types of research report with example

• Research Report: Definition, Types + [Writing Guide]

One of the reasons for carrying out research is to add to the existing body of knowledge. Therefore, when conducting research, you need to document your processes and findings in a research report. 

With a research report, it is easy to outline the findings of your systematic investigation and any gaps needing further inquiry. Knowing how to create a detailed research report will prove useful when you need to conduct research.  

What is a Research Report?

A research report is a well-crafted document that outlines the processes, data, and findings of a systematic investigation. It is an important document that serves as a first-hand account of the research process, and it is typically considered an objective and accurate source of information.

In many ways, a research report can be considered as a summary of the research process that clearly highlights findings, recommendations, and other important details. Reading a well-written research report should provide you with all the information you need about the core areas of the research process.

Features of a Research Report 

So how do you recognize a research report when you see one? Here are some of the basic features that define a research report. 

• It is a detailed presentation of research processes and findings, and it usually includes tables and graphs. 
• It is written in a formal language.
• A research report is usually written in the third person.
• It is informative and based on first-hand verifiable information.
• It is formally structured with headings, sections, and bullet points.
• It always includes recommendations for future actions. 

Types of Research Report 

The research report is classified based on two things; nature of research and target audience.

Nature of Research

• Qualitative Research Report

This is the type of report written for qualitative research . It outlines the methods, processes, and findings of a qualitative method of systematic investigation. In educational research, a qualitative research report provides an opportunity for one to apply his or her knowledge and develop skills in planning and executing qualitative research projects.

A qualitative research report is usually descriptive in nature. Hence, in addition to presenting details of the research process, you must also create a descriptive narrative of the information.

• Quantitative Research Report

A quantitative research report is a type of research report that is written for quantitative research. Quantitative research is a type of systematic investigation that pays attention to numerical or statistical values in a bid to find answers to research questions. 

In this type of research report, the researcher presents quantitative data to support the research process and findings. Unlike a qualitative research report that is mainly descriptive, a quantitative research report works with numbers; that is, it is numerical in nature. 

Target Audience

Also, a research report can be said to be technical or popular based on the target audience. If you’re dealing with a general audience, you would need to present a popular research report, and if you’re dealing with a specialized audience, you would submit a technical report. 

• Technical Research Report

A technical research report is a detailed document that you present after carrying out industry-based research. This report is highly specialized because it provides information for a technical audience; that is, individuals with above-average knowledge in the field of study. 

In a technical research report, the researcher is expected to provide specific information about the research process, including statistical analyses and sampling methods. Also, the use of language is highly specialized and filled with jargon. 

Examples of technical research reports include legal and medical research reports. 

• Popular Research Report

A popular research report is one for a general audience; that is, for individuals who do not necessarily have any knowledge in the field of study. A popular research report aims to make information accessible to everyone. 

It is written in very simple language, which makes it easy to understand the findings and recommendations. Examples of popular research reports are the information contained in newspapers and magazines. 

Importance of a Research Report 

• Knowledge Transfer: As already stated above, one of the reasons for carrying out research is to contribute to the existing body of knowledge, and this is made possible with a research report. A research report serves as a means to effectively communicate the findings of a systematic investigation to all and sundry.  
• Identification of Knowledge Gaps: With a research report, you’d be able to identify knowledge gaps for further inquiry. A research report shows what has been done while hinting at other areas needing systematic investigation. 
• In market research, a research report would help you understand the market needs and peculiarities at a glance. 
• A research report allows you to present information in a precise and concise manner. 
• It is time-efficient and practical because, in a research report, you do not have to spend time detailing the findings of your research work in person. You can easily send out the report via email and have stakeholders look at it. 

Guide to Writing a Research Report

A lot of detail goes into writing a research report, and getting familiar with the different requirements would help you create the ideal research report. A research report is usually broken down into multiple sections, which allows for a concise presentation of information.

Structure and Example of a Research Report

This is the title of your systematic investigation. Your title should be concise and point to the aims, objectives, and findings of a research report. 

• Table of Contents

This is like a compass that makes it easier for readers to navigate the research report.

An abstract is an overview that highlights all important aspects of the research including the research method, data collection process, and research findings. Think of an abstract as a summary of your research report that presents pertinent information in a concise manner. 

An abstract is always brief; typically 100-150 words and goes straight to the point. The focus of your research abstract should be the 5Ws and 1H format – What, Where, Why, When, Who and How. 

• Introduction

Here, the researcher highlights the aims and objectives of the systematic investigation as well as the problem which the systematic investigation sets out to solve. When writing the report introduction, it is also essential to indicate whether the purposes of the research were achieved or would require more work.

In the introduction section, the researcher specifies the research problem and also outlines the significance of the systematic investigation. Also, the researcher is expected to outline any jargons and terminologies that are contained in the research.  

• Literature Review

A literature review is a written survey of existing knowledge in the field of study. In other words, it is the section where you provide an overview and analysis of different research works that are relevant to your systematic investigation. 

It highlights existing research knowledge and areas needing further investigation, which your research has sought to fill. At this stage, you can also hint at your research hypothesis and its possible implications for the existing body of knowledge in your field of study. 

• An Account of Investigation

This is a detailed account of the research process, including the methodology, sample, and research subjects. Here, you are expected to provide in-depth information on the research process including the data collection and analysis procedures. 

In a quantitative research report, you’d need to provide information surveys, questionnaires and other quantitative data collection methods used in your research. In a qualitative research report, you are expected to describe the qualitative data collection methods used in your research including interviews and focus groups. 

In this section, you are expected to present the results of the systematic investigation. 

This section further explains the findings of the research, earlier outlined. Here, you are expected to present a justification for each outcome and show whether the results are in line with your hypotheses or if other research studies have come up with similar results.

• Conclusions

This is a summary of all the information in the report. It also outlines the significance of the entire study. 

• References and Appendices

This section contains a list of all the primary and secondary research sources. 

Tips for Writing a Research Report

• Define the Context for the Report

As is obtainable when writing an essay, defining the context for your research report would help you create a detailed yet concise document. This is why you need to create an outline before writing so that you do not miss out on anything. 

• Define your Audience

Writing with your audience in mind is essential as it determines the tone of the report. If you’re writing for a general audience, you would want to present the information in a simple and relatable manner. For a specialized audience, you would need to make use of technical and field-specific terms. 

• Include Significant Findings

The idea of a research report is to present some sort of abridged version of your systematic investigation. In your report, you should exclude irrelevant information while highlighting only important data and findings. 

• Include Illustrations

Your research report should include illustrations and other visual representations of your data. Graphs, pie charts, and relevant images lend additional credibility to your systematic investigation.

• Choose the Right Title

A good research report title is brief, precise, and contains keywords from your research. It should provide a clear idea of your systematic investigation so that readers can grasp the entire focus of your research from the title. 

• Proofread the Report

Before publishing the document, ensure that you give it a second look to authenticate the information. If you can, get someone else to go through the report, too, and you can also run it through proofreading and editing software. 

How to Gather Research Data for Your Report  

• Understand the Problem

Every research aims at solving a specific problem or set of problems, and this should be at the back of your mind when writing your research report. Understanding the problem would help you to filter the information you have and include only important data in your report. 

• Know what your report seeks to achieve

This is somewhat similar to the point above because, in some way, the aim of your research report is intertwined with the objectives of your systematic investigation. Identifying the primary purpose of writing a research report would help you to identify and present the required information accordingly. 

• Identify your audience

Knowing your target audience plays a crucial role in data collection for a research report. If your research report is specifically for an organization, you would want to present industry-specific information or show how the research findings are relevant to the work that the company does. 

• Create Surveys/Questionnaires

A survey is a research method that is used to gather data from a specific group of people through a set of questions. It can be either quantitative or qualitative. 

A survey is usually made up of structured questions, and it can be administered online or offline. However, an online survey is a more effective method of research data collection because it helps you save time and gather data with ease. 

You can seamlessly create an online questionnaire for your research on Formplus . With the multiple sharing options available in the builder, you would be able to administer your survey to respondents in little or no time. 

Formplus also has a report summary too l that you can use to create custom visual reports for your research.

Step-by-step guide on how to create an online questionnaire using Formplus  

• Sign into Formplus

In the Formplus builder, you can easily create different online questionnaires for your research by dragging and dropping preferred fields into your form. To access the Formplus builder, you will need to create an account on Formplus. 

Once you do this, sign in to your account and click on Create new form to begin. 

• Edit Form Title : Click on the field provided to input your form title, for example, “Research Questionnaire.”
• Edit Form : Click on the edit icon to edit the form.
• Add Fields : Drag and drop preferred form fields into your form in the Formplus builder inputs column. There are several field input options for questionnaires in the Formplus builder. 
• Edit fields
• Click on “Save”
• Form Customization: With the form customization options in the form builder, you can easily change the outlook of your form and make it more unique and personalized. Formplus allows you to change your form theme, add background images, and even change the font according to your needs. 
• Multiple Sharing Options: Formplus offers various form-sharing options, which enables you to share your questionnaire with respondents easily. You can use the direct social media sharing buttons to share your form link to your organization’s social media pages.  You can also send out your survey form as email invitations to your research subjects too. If you wish, you can share your form’s QR code or embed it on your organization’s website for easy access. 

Conclusion  

Always remember that a research report is just as important as the actual systematic investigation because it plays a vital role in communicating research findings to everyone else. This is why you must take care to create a concise document summarizing the process of conducting any research. 

In this article, we’ve outlined essential tips to help you create a research report. When writing your report, you should always have the audience at the back of your mind, as this would set the tone for the document. 

Connect to Formplus, Get Started Now - It's Free!

• ethnographic research survey
• research report
• research report survey
• busayo.longe

You may also like:

How to Write a Problem Statement for your Research

Learn how to write problem statements before commencing any research effort. Learn about its structure and explore examples

Ethnographic Research: Types, Methods + [Question Examples]

Simple guide on ethnographic research, it types, methods, examples and advantages. Also highlights how to conduct an ethnographic...

21 Chrome Extensions for Academic Researchers in 2022

In this article, we will discuss a number of chrome extensions you can use to make your research process even seamless

Assessment Tools: Types, Examples & Importance

In this article, you’ll learn about different assessment tools to help you evaluate performance in various contexts

Formplus - For Seamless Data Collection

Collect data the right way with a versatile data collection tool. try formplus and transform your work productivity today..

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

Chapter 11: Presenting Your Research

Writing a Research Report in American Psychological Association (APA) Style

Learning Objectives

• Identify the major sections of an APA-style research report and the basic contents of each section.
• Plan and write an effective APA-style research report.

In this section, we look at how to write an APA-style empirical research report , an article that presents the results of one or more new studies. Recall that the standard sections of an empirical research report provide a kind of outline. Here we consider each of these sections in detail, including what information it contains, how that information is formatted and organized, and tips for writing each section. At the end of this section is a sample APA-style research report that illustrates many of these principles.

Sections of a Research Report

Title page and abstract.

An APA-style research report begins with a  title page . The title is centred in the upper half of the page, with each important word capitalized. The title should clearly and concisely (in about 12 words or fewer) communicate the primary variables and research questions. This sometimes requires a main title followed by a subtitle that elaborates on the main title, in which case the main title and subtitle are separated by a colon. Here are some titles from recent issues of professional journals published by the American Psychological Association.

• Sex Differences in Coping Styles and Implications for Depressed Mood
• Effects of Aging and Divided Attention on Memory for Items and Their Contexts
• Computer-Assisted Cognitive Behavioural Therapy for Child Anxiety: Results of a Randomized Clinical Trial
• Virtual Driving and Risk Taking: Do Racing Games Increase Risk-Taking Cognitions, Affect, and Behaviour?

Below the title are the authors’ names and, on the next line, their institutional affiliation—the university or other institution where the authors worked when they conducted the research. As we have already seen, the authors are listed in an order that reflects their contribution to the research. When multiple authors have made equal contributions to the research, they often list their names alphabetically or in a randomly determined order.

In some areas of psychology, the titles of many empirical research reports are informal in a way that is perhaps best described as “cute.” They usually take the form of a play on words or a well-known expression that relates to the topic under study. Here are some examples from recent issues of the Journal Psychological Science .

• “Smells Like Clean Spirit: Nonconscious Effects of Scent on Cognition and Behavior”
• “Time Crawls: The Temporal Resolution of Infants’ Visual Attention”
• “Scent of a Woman: Men’s Testosterone Responses to Olfactory Ovulation Cues”
• “Apocalypse Soon?: Dire Messages Reduce Belief in Global Warming by Contradicting Just-World Beliefs”
• “Serial vs. Parallel Processing: Sometimes They Look Like Tweedledum and Tweedledee but They Can (and Should) Be Distinguished”
• “How Do I Love Thee? Let Me Count the Words: The Social Effects of Expressive Writing”

Individual researchers differ quite a bit in their preference for such titles. Some use them regularly, while others never use them. What might be some of the pros and cons of using cute article titles?

For articles that are being submitted for publication, the title page also includes an author note that lists the authors’ full institutional affiliations, any acknowledgments the authors wish to make to agencies that funded the research or to colleagues who commented on it, and contact information for the authors. For student papers that are not being submitted for publication—including theses—author notes are generally not necessary.

The  abstract  is a summary of the study. It is the second page of the manuscript and is headed with the word  Abstract . The first line is not indented. The abstract presents the research question, a summary of the method, the basic results, and the most important conclusions. Because the abstract is usually limited to about 200 words, it can be a challenge to write a good one.

Introduction

The  introduction  begins on the third page of the manuscript. The heading at the top of this page is the full title of the manuscript, with each important word capitalized as on the title page. The introduction includes three distinct subsections, although these are typically not identified by separate headings. The opening introduces the research question and explains why it is interesting, the literature review discusses relevant previous research, and the closing restates the research question and comments on the method used to answer it.

The Opening

The  opening , which is usually a paragraph or two in length, introduces the research question and explains why it is interesting. To capture the reader’s attention, researcher Daryl Bem recommends starting with general observations about the topic under study, expressed in ordinary language (not technical jargon)—observations that are about people and their behaviour (not about researchers or their research; Bem, 2003 [1] ). Concrete examples are often very useful here. According to Bem, this would be a poor way to begin a research report:

Festinger’s theory of cognitive dissonance received a great deal of attention during the latter part of the 20th century (p. 191)

The following would be much better:

The individual who holds two beliefs that are inconsistent with one another may feel uncomfortable. For example, the person who knows that he or she enjoys smoking but believes it to be unhealthy may experience discomfort arising from the inconsistency or disharmony between these two thoughts or cognitions. This feeling of discomfort was called cognitive dissonance by social psychologist Leon Festinger (1957), who suggested that individuals will be motivated to remove this dissonance in whatever way they can (p. 191).

After capturing the reader’s attention, the opening should go on to introduce the research question and explain why it is interesting. Will the answer fill a gap in the literature? Will it provide a test of an important theory? Does it have practical implications? Giving readers a clear sense of what the research is about and why they should care about it will motivate them to continue reading the literature review—and will help them make sense of it.

Breaking the Rules

Researcher Larry Jacoby reported several studies showing that a word that people see or hear repeatedly can seem more familiar even when they do not recall the repetitions—and that this tendency is especially pronounced among older adults. He opened his article with the following humourous anecdote:

A friend whose mother is suffering symptoms of Alzheimer’s disease (AD) tells the story of taking her mother to visit a nursing home, preliminary to her mother’s moving there. During an orientation meeting at the nursing home, the rules and regulations were explained, one of which regarded the dining room. The dining room was described as similar to a fine restaurant except that tipping was not required. The absence of tipping was a central theme in the orientation lecture, mentioned frequently to emphasize the quality of care along with the advantages of having paid in advance. At the end of the meeting, the friend’s mother was asked whether she had any questions. She replied that she only had one question: “Should I tip?” (Jacoby, 1999, p. 3)

Although both humour and personal anecdotes are generally discouraged in APA-style writing, this example is a highly effective way to start because it both engages the reader and provides an excellent real-world example of the topic under study.

The Literature Review

Immediately after the opening comes the  literature review , which describes relevant previous research on the topic and can be anywhere from several paragraphs to several pages in length. However, the literature review is not simply a list of past studies. Instead, it constitutes a kind of argument for why the research question is worth addressing. By the end of the literature review, readers should be convinced that the research question makes sense and that the present study is a logical next step in the ongoing research process.

Like any effective argument, the literature review must have some kind of structure. For example, it might begin by describing a phenomenon in a general way along with several studies that demonstrate it, then describing two or more competing theories of the phenomenon, and finally presenting a hypothesis to test one or more of the theories. Or it might describe one phenomenon, then describe another phenomenon that seems inconsistent with the first one, then propose a theory that resolves the inconsistency, and finally present a hypothesis to test that theory. In applied research, it might describe a phenomenon or theory, then describe how that phenomenon or theory applies to some important real-world situation, and finally suggest a way to test whether it does, in fact, apply to that situation.

Looking at the literature review in this way emphasizes a few things. First, it is extremely important to start with an outline of the main points that you want to make, organized in the order that you want to make them. The basic structure of your argument, then, should be apparent from the outline itself. Second, it is important to emphasize the structure of your argument in your writing. One way to do this is to begin the literature review by summarizing your argument even before you begin to make it. “In this article, I will describe two apparently contradictory phenomena, present a new theory that has the potential to resolve the apparent contradiction, and finally present a novel hypothesis to test the theory.” Another way is to open each paragraph with a sentence that summarizes the main point of the paragraph and links it to the preceding points. These opening sentences provide the “transitions” that many beginning researchers have difficulty with. Instead of beginning a paragraph by launching into a description of a previous study, such as “Williams (2004) found that…,” it is better to start by indicating something about why you are describing this particular study. Here are some simple examples:

Another example of this phenomenon comes from the work of Williams (2004).

Williams (2004) offers one explanation of this phenomenon.

An alternative perspective has been provided by Williams (2004).

We used a method based on the one used by Williams (2004).

Finally, remember that your goal is to construct an argument for why your research question is interesting and worth addressing—not necessarily why your favourite answer to it is correct. In other words, your literature review must be balanced. If you want to emphasize the generality of a phenomenon, then of course you should discuss various studies that have demonstrated it. However, if there are other studies that have failed to demonstrate it, you should discuss them too. Or if you are proposing a new theory, then of course you should discuss findings that are consistent with that theory. However, if there are other findings that are inconsistent with it, again, you should discuss them too. It is acceptable to argue that the  balance  of the research supports the existence of a phenomenon or is consistent with a theory (and that is usually the best that researchers in psychology can hope for), but it is not acceptable to  ignore contradictory evidence. Besides, a large part of what makes a research question interesting is uncertainty about its answer.

The Closing

The  closing  of the introduction—typically the final paragraph or two—usually includes two important elements. The first is a clear statement of the main research question or hypothesis. This statement tends to be more formal and precise than in the opening and is often expressed in terms of operational definitions of the key variables. The second is a brief overview of the method and some comment on its appropriateness. Here, for example, is how Darley and Latané (1968) [2] concluded the introduction to their classic article on the bystander effect:

These considerations lead to the hypothesis that the more bystanders to an emergency, the less likely, or the more slowly, any one bystander will intervene to provide aid. To test this proposition it would be necessary to create a situation in which a realistic “emergency” could plausibly occur. Each subject should also be blocked from communicating with others to prevent his getting information about their behaviour during the emergency. Finally, the experimental situation should allow for the assessment of the speed and frequency of the subjects’ reaction to the emergency. The experiment reported below attempted to fulfill these conditions. (p. 378)

Thus the introduction leads smoothly into the next major section of the article—the method section.

The  method section  is where you describe how you conducted your study. An important principle for writing a method section is that it should be clear and detailed enough that other researchers could replicate the study by following your “recipe.” This means that it must describe all the important elements of the study—basic demographic characteristics of the participants, how they were recruited, whether they were randomly assigned, how the variables were manipulated or measured, how counterbalancing was accomplished, and so on. At the same time, it should avoid irrelevant details such as the fact that the study was conducted in Classroom 37B of the Industrial Technology Building or that the questionnaire was double-sided and completed using pencils.

The method section begins immediately after the introduction ends with the heading “Method” (not “Methods”) centred on the page. Immediately after this is the subheading “Participants,” left justified and in italics. The participants subsection indicates how many participants there were, the number of women and men, some indication of their age, other demographics that may be relevant to the study, and how they were recruited, including any incentives given for participation.

After the participants section, the structure can vary a bit. Figure 11.1 shows three common approaches. In the first, the participants section is followed by a design and procedure subsection, which describes the rest of the method. This works well for methods that are relatively simple and can be described adequately in a few paragraphs. In the second approach, the participants section is followed by separate design and procedure subsections. This works well when both the design and the procedure are relatively complicated and each requires multiple paragraphs.

What is the difference between design and procedure? The design of a study is its overall structure. What were the independent and dependent variables? Was the independent variable manipulated, and if so, was it manipulated between or within subjects? How were the variables operationally defined? The procedure is how the study was carried out. It often works well to describe the procedure in terms of what the participants did rather than what the researchers did. For example, the participants gave their informed consent, read a set of instructions, completed a block of four practice trials, completed a block of 20 test trials, completed two questionnaires, and were debriefed and excused.

In the third basic way to organize a method section, the participants subsection is followed by a materials subsection before the design and procedure subsections. This works well when there are complicated materials to describe. This might mean multiple questionnaires, written vignettes that participants read and respond to, perceptual stimuli, and so on. The heading of this subsection can be modified to reflect its content. Instead of “Materials,” it can be “Questionnaires,” “Stimuli,” and so on.

The  results section  is where you present the main results of the study, including the results of the statistical analyses. Although it does not include the raw data—individual participants’ responses or scores—researchers should save their raw data and make them available to other researchers who request them. Several journals now encourage the open sharing of raw data online.

Although there are no standard subsections, it is still important for the results section to be logically organized. Typically it begins with certain preliminary issues. One is whether any participants or responses were excluded from the analyses and why. The rationale for excluding data should be described clearly so that other researchers can decide whether it is appropriate. A second preliminary issue is how multiple responses were combined to produce the primary variables in the analyses. For example, if participants rated the attractiveness of 20 stimulus people, you might have to explain that you began by computing the mean attractiveness rating for each participant. Or if they recalled as many items as they could from study list of 20 words, did you count the number correctly recalled, compute the percentage correctly recalled, or perhaps compute the number correct minus the number incorrect? A third preliminary issue is the reliability of the measures. This is where you would present test-retest correlations, Cronbach’s α, or other statistics to show that the measures are consistent across time and across items. A final preliminary issue is whether the manipulation was successful. This is where you would report the results of any manipulation checks.

The results section should then tackle the primary research questions, one at a time. Again, there should be a clear organization. One approach would be to answer the most general questions and then proceed to answer more specific ones. Another would be to answer the main question first and then to answer secondary ones. Regardless, Bem (2003) [3] suggests the following basic structure for discussing each new result:

• Remind the reader of the research question.
• Give the answer to the research question in words.
• Present the relevant statistics.
• Qualify the answer if necessary.
• Summarize the result.

Notice that only Step 3 necessarily involves numbers. The rest of the steps involve presenting the research question and the answer to it in words. In fact, the basic results should be clear even to a reader who skips over the numbers.

The  discussion  is the last major section of the research report. Discussions usually consist of some combination of the following elements:

• Summary of the research
• Theoretical implications
• Practical implications
• Limitations
• Suggestions for future research

The discussion typically begins with a summary of the study that provides a clear answer to the research question. In a short report with a single study, this might require no more than a sentence. In a longer report with multiple studies, it might require a paragraph or even two. The summary is often followed by a discussion of the theoretical implications of the research. Do the results provide support for any existing theories? If not, how  can  they be explained? Although you do not have to provide a definitive explanation or detailed theory for your results, you at least need to outline one or more possible explanations. In applied research—and often in basic research—there is also some discussion of the practical implications of the research. How can the results be used, and by whom, to accomplish some real-world goal?

The theoretical and practical implications are often followed by a discussion of the study’s limitations. Perhaps there are problems with its internal or external validity. Perhaps the manipulation was not very effective or the measures not very reliable. Perhaps there is some evidence that participants did not fully understand their task or that they were suspicious of the intent of the researchers. Now is the time to discuss these issues and how they might have affected the results. But do not overdo it. All studies have limitations, and most readers will understand that a different sample or different measures might have produced different results. Unless there is good reason to think they  would have, however, there is no reason to mention these routine issues. Instead, pick two or three limitations that seem like they could have influenced the results, explain how they could have influenced the results, and suggest ways to deal with them.

Most discussions end with some suggestions for future research. If the study did not satisfactorily answer the original research question, what will it take to do so? What  new  research questions has the study raised? This part of the discussion, however, is not just a list of new questions. It is a discussion of two or three of the most important unresolved issues. This means identifying and clarifying each question, suggesting some alternative answers, and even suggesting ways they could be studied.

Finally, some researchers are quite good at ending their articles with a sweeping or thought-provoking conclusion. Darley and Latané (1968) [4] , for example, ended their article on the bystander effect by discussing the idea that whether people help others may depend more on the situation than on their personalities. Their final sentence is, “If people understand the situational forces that can make them hesitate to intervene, they may better overcome them” (p. 383). However, this kind of ending can be difficult to pull off. It can sound overreaching or just banal and end up detracting from the overall impact of the article. It is often better simply to end when you have made your final point (although you should avoid ending on a limitation).

The references section begins on a new page with the heading “References” centred at the top of the page. All references cited in the text are then listed in the format presented earlier. They are listed alphabetically by the last name of the first author. If two sources have the same first author, they are listed alphabetically by the last name of the second author. If all the authors are the same, then they are listed chronologically by the year of publication. Everything in the reference list is double-spaced both within and between references.

Appendices, Tables, and Figures

Appendices, tables, and figures come after the references. An  appendix  is appropriate for supplemental material that would interrupt the flow of the research report if it were presented within any of the major sections. An appendix could be used to present lists of stimulus words, questionnaire items, detailed descriptions of special equipment or unusual statistical analyses, or references to the studies that are included in a meta-analysis. Each appendix begins on a new page. If there is only one, the heading is “Appendix,” centred at the top of the page. If there is more than one, the headings are “Appendix A,” “Appendix B,” and so on, and they appear in the order they were first mentioned in the text of the report.

After any appendices come tables and then figures. Tables and figures are both used to present results. Figures can also be used to illustrate theories (e.g., in the form of a flowchart), display stimuli, outline procedures, and present many other kinds of information. Each table and figure appears on its own page. Tables are numbered in the order that they are first mentioned in the text (“Table 1,” “Table 2,” and so on). Figures are numbered the same way (“Figure 1,” “Figure 2,” and so on). A brief explanatory title, with the important words capitalized, appears above each table. Each figure is given a brief explanatory caption, where (aside from proper nouns or names) only the first word of each sentence is capitalized. More details on preparing APA-style tables and figures are presented later in the book.

Sample APA-Style Research Report

Figures 11.2, 11.3, 11.4, and 11.5 show some sample pages from an APA-style empirical research report originally written by undergraduate student Tomoe Suyama at California State University, Fresno. The main purpose of these figures is to illustrate the basic organization and formatting of an APA-style empirical research report, although many high-level and low-level style conventions can be seen here too.

Key Takeaways

• An APA-style empirical research report consists of several standard sections. The main ones are the abstract, introduction, method, results, discussion, and references.
• The introduction consists of an opening that presents the research question, a literature review that describes previous research on the topic, and a closing that restates the research question and comments on the method. The literature review constitutes an argument for why the current study is worth doing.
• The method section describes the method in enough detail that another researcher could replicate the study. At a minimum, it consists of a participants subsection and a design and procedure subsection.
• The results section describes the results in an organized fashion. Each primary result is presented in terms of statistical results but also explained in words.
• The discussion typically summarizes the study, discusses theoretical and practical implications and limitations of the study, and offers suggestions for further research.
• Practice: Look through an issue of a general interest professional journal (e.g.,  Psychological Science ). Read the opening of the first five articles and rate the effectiveness of each one from 1 ( very ineffective ) to 5 ( very effective ). Write a sentence or two explaining each rating.
• Practice: Find a recent article in a professional journal and identify where the opening, literature review, and closing of the introduction begin and end.
• Practice: Find a recent article in a professional journal and highlight in a different colour each of the following elements in the discussion: summary, theoretical implications, practical implications, limitations, and suggestions for future research.

Long Descriptions

Figure 11.1 long description: Table showing three ways of organizing an APA-style method section.

In the simple method, there are two subheadings: “Participants” (which might begin “The participants were…”) and “Design and procedure” (which might begin “There were three conditions…”).

In the typical method, there are three subheadings: “Participants” (“The participants were…”), “Design” (“There were three conditions…”), and “Procedure” (“Participants viewed each stimulus on the computer screen…”).

In the complex method, there are four subheadings: “Participants” (“The participants were…”), “Materials” (“The stimuli were…”), “Design” (“There were three conditions…”), and “Procedure” (“Participants viewed each stimulus on the computer screen…”). [Return to Figure 11.1]

• Bem, D. J. (2003). Writing the empirical journal article. In J. M. Darley, M. P. Zanna, & H. R. Roediger III (Eds.),  The compleat academic: A practical guide for the beginning social scientist  (2nd ed.). Washington, DC: American Psychological Association. ↵
• Darley, J. M., & Latané, B. (1968). Bystander intervention in emergencies: Diffusion of responsibility.  Journal of Personality and Social Psychology, 4 , 377–383. ↵

A type of research article which describes one or more new empirical studies conducted by the authors.

The page at the beginning of an APA-style research report containing the title of the article, the authors’ names, and their institutional affiliation.

A summary of a research study.

The third page of a manuscript containing the research question, the literature review, and comments about how to answer the research question.

An introduction to the research question and explanation for why this question is interesting.

A description of relevant previous research on the topic being discusses and an argument for why the research is worth addressing.

The end of the introduction, where the research question is reiterated and the method is commented upon.

The section of a research report where the method used to conduct the study is described.

The main results of the study, including the results from statistical analyses, are presented in a research article.

Section of a research report that summarizes the study's results and interprets them by referring back to the study's theoretical background.

Part of a research report which contains supplemental material.

Research Methods in Psychology - 2nd Canadian Edition Copyright © 2015 by Paul C. Price, Rajiv Jhangiani, & I-Chant A. Chiang is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Share This Book

• Skip to main content
• Skip to primary sidebar
• Skip to footer
• QuestionPro

• Solutions Industries Gaming Automotive Sports and events Education Government Travel & Hospitality Financial Services Healthcare Cannabis Technology Use Case NPS+ Communities Audience Contactless surveys Mobile LivePolls Member Experience GDPR Positive People Science 360 Feedback Surveys
• Resources Blog eBooks Survey Templates Case Studies Training Help center

Home Market Research

Research Reports: Definition and How to Write Them

Reports are usually spread across a vast horizon of topics but are focused on communicating information about a particular topic and a niche target market. The primary motive of research reports is to convey integral details about a study for marketers to consider while designing new strategies.

Certain events, facts, and other information based on incidents need to be relayed to the people in charge, and creating research reports is the most effective communication tool. Ideal research reports are extremely accurate in the offered information with a clear objective and conclusion. These reports should have a clean and structured format to relay information effectively.

What are Research Reports?

Research reports are recorded data prepared by researchers or statisticians after analyzing the information gathered by conducting organized research, typically in the form of surveys or qualitative methods .

A research report is a reliable source to recount details about a conducted research. It is most often considered to be a true testimony of all the work done to garner specificities of research.

The various sections of a research report are:

• Background/Introduction
• Implemented Methods
• Results based on Analysis
• Deliberation

Learn more: Quantitative Research

Components of Research Reports

Research is imperative for launching a new product/service or a new feature. The markets today are extremely volatile and competitive due to new entrants every day who may or may not provide effective products. An organization needs to make the right decisions at the right time to be relevant in such a market with updated products that suffice customer demands.

The details of a research report may change with the purpose of research but the main components of a report will remain constant. The research approach of the market researcher also influences the style of writing reports. Here are seven main components of a productive research report:

• Research Report Summary: The entire objective along with the overview of research are to be included in a summary which is a couple of paragraphs in length. All the multiple components of the research are explained in brief under the report summary.  It should be interesting enough to capture all the key elements of the report.
• Research Introduction: There always is a primary goal that the researcher is trying to achieve through a report. In the introduction section, he/she can cover answers related to this goal and establish a thesis which will be included to strive and answer it in detail.  This section should answer an integral question: “What is the current situation of the goal?”.  After the research design was conducted, did the organization conclude the goal successfully or they are still a work in progress –  provide such details in the introduction part of the research report.
• Research Methodology: This is the most important section of the report where all the important information lies. The readers can gain data for the topic along with analyzing the quality of provided content and the research can also be approved by other market researchers . Thus, this section needs to be highly informative with each aspect of research discussed in detail.  Information needs to be expressed in chronological order according to its priority and importance. Researchers should include references in case they gained information from existing techniques.
• Research Results: A short description of the results along with calculations conducted to achieve the goal will form this section of results. Usually, the exposition after data analysis is carried out in the discussion part of the report.

Learn more: Quantitative Data

• Research Discussion: The results are discussed in extreme detail in this section along with a comparative analysis of reports that could probably exist in the same domain. Any abnormality uncovered during research will be deliberated in the discussion section.  While writing research reports, the researcher will have to connect the dots on how the results will be applicable in the real world.
• Research References and Conclusion: Conclude all the research findings along with mentioning each and every author, article or any content piece from where references were taken.

Learn more: Qualitative Observation

15 Tips for Writing Research Reports

Writing research reports in the manner can lead to all the efforts going down the drain. Here are 15 tips for writing impactful research reports:

• Prepare the context before starting to write and start from the basics:  This was always taught to us in school – be well-prepared before taking a plunge into new topics. The order of survey questions might not be the ideal or most effective order for writing research reports. The idea is to start with a broader topic and work towards a more specific one and focus on a conclusion or support, which a research should support with the facts.  The most difficult thing to do in reporting, without a doubt is to start. Start with the title, the introduction, then document the first discoveries and continue from that. Once the marketers have the information well documented, they can write a general conclusion.
• Keep the target audience in mind while selecting a format that is clear, logical and obvious to them:  Will the research reports be presented to decision makers or other researchers? What are the general perceptions around that topic? This requires more care and diligence. A researcher will need a significant amount of information to start writing the research report. Be consistent with the wording, the numbering of the annexes and so on. Follow the approved format of the company for the delivery of research reports and demonstrate the integrity of the project with the objectives of the company.
• Have a clear research objective: A researcher should read the entire proposal again, and make sure that the data they provide contributes to the objectives that were raised from the beginning. Remember that speculations are for conversations, not for research reports, if a researcher speculates, they directly question their own research.
• Establish a working model:  Each study must have an internal logic, which will have to be established in the report and in the evidence. The researchers’ worst nightmare is to be required to write research reports and realize that key questions were not included.

Learn more: Quantitative Observation

• Gather all the information about the research topic. Who are the competitors of our customers? Talk to other researchers who have studied the subject of research, know the language of the industry. Misuse of the terms can discourage the readers of research reports from reading further.
• Read aloud while writing. While reading the report, if the researcher hears something inappropriate, for example, if they stumble over the words when reading them, surely the reader will too. If the researcher can’t put an idea in a single sentence, then it is very long and they must change it so that the idea is clear to everyone.
• Check grammar and spelling. Without a doubt, good practices help to understand the report. Use verbs in the present tense. Consider using the present tense, which makes the results sound more immediate. Find new words and other ways of saying things. Have fun with the language whenever possible.
• Discuss only the discoveries that are significant. If some data are not really significant, do not mention them. Remember that not everything is truly important or essential within research reports.

Learn more: Qualitative Data

• Try and stick to the survey questions. For example, do not say that the people surveyed “were worried” about an research issue , when there are different degrees of concern.
• The graphs must be clear enough so that they understand themselves. Do not let graphs lead the reader to make mistakes: give them a title, include the indications, the size of the sample, and the correct wording of the question.
• Be clear with messages. A researcher should always write every section of the report with an accuracy of details and language.
• Be creative with titles – Particularly in segmentation studies choose names “that give life to research”. Such names can survive for a long time after the initial investigation.
• Create an effective conclusion: The conclusion in the research reports is the most difficult to write, but it is an incredible opportunity to excel. Make a precise summary. Sometimes it helps to start the conclusion with something specific, then it describes the most important part of the study, and finally, it provides the implications of the conclusions.
• Get a couple more pair of eyes to read the report. Writers have trouble detecting their own mistakes. But they are responsible for what is presented. Ensure it has been approved by colleagues or friends before sending the find draft out.

Learn more: Market Research and Analysis

MORE LIKE THIS

How Can I Help You? — Tuesday CX Thoughts

Jun 5, 2024

Why Multilingual 360 Feedback Surveys Provide Better Insights

Jun 3, 2024

Raked Weighting: A Key Tool for Accurate Survey Results

May 31, 2024

Top 8 Data Trends to Understand the Future of Data

May 30, 2024

Other categories

• Academic Research
• Artificial Intelligence
• Assessments
• Brand Awareness
• Case Studies
• Communities
• Consumer Insights
• Customer effort score
• Customer Engagement
• Customer Experience
• Customer Loyalty
• Customer Research
• Customer Satisfaction
• Employee Benefits
• Employee Engagement
• Employee Retention
• Friday Five
• General Data Protection Regulation
• Insights Hub
• Life@QuestionPro
• Market Research
• Mobile diaries
• Mobile Surveys
• New Features
• Online Communities
• Question Types
• Questionnaire
• QuestionPro Products
• Release Notes
• Research Tools and Apps
• Revenue at Risk
• Survey Templates
• Training Tips
• Uncategorized
• Video Learning Series
• What’s Coming Up
• Workforce Intelligence

Scientific Reports

What this handout is about.

This handout provides a general guide to writing reports about scientific research you’ve performed. In addition to describing the conventional rules about the format and content of a lab report, we’ll also attempt to convey why these rules exist, so you’ll get a clearer, more dependable idea of how to approach this writing situation. Readers of this handout may also find our handout on writing in the sciences useful.

Background and pre-writing

Why do we write research reports.

You did an experiment or study for your science class, and now you have to write it up for your teacher to review. You feel that you understood the background sufficiently, designed and completed the study effectively, obtained useful data, and can use those data to draw conclusions about a scientific process or principle. But how exactly do you write all that? What is your teacher expecting to see?

To take some of the guesswork out of answering these questions, try to think beyond the classroom setting. In fact, you and your teacher are both part of a scientific community, and the people who participate in this community tend to share the same values. As long as you understand and respect these values, your writing will likely meet the expectations of your audience—including your teacher.

So why are you writing this research report? The practical answer is “Because the teacher assigned it,” but that’s classroom thinking. Generally speaking, people investigating some scientific hypothesis have a responsibility to the rest of the scientific world to report their findings, particularly if these findings add to or contradict previous ideas. The people reading such reports have two primary goals:

• They want to gather the information presented.
• They want to know that the findings are legitimate.

Your job as a writer, then, is to fulfill these two goals.

How do I do that?

Good question. Here is the basic format scientists have designed for research reports:

• Introduction

Methods and Materials

This format, sometimes called “IMRAD,” may take slightly different shapes depending on the discipline or audience; some ask you to include an abstract or separate section for the hypothesis, or call the Discussion section “Conclusions,” or change the order of the sections (some professional and academic journals require the Methods section to appear last). Overall, however, the IMRAD format was devised to represent a textual version of the scientific method.

The scientific method, you’ll probably recall, involves developing a hypothesis, testing it, and deciding whether your findings support the hypothesis. In essence, the format for a research report in the sciences mirrors the scientific method but fleshes out the process a little. Below, you’ll find a table that shows how each written section fits into the scientific method and what additional information it offers the reader.

Thinking of your research report as based on the scientific method, but elaborated in the ways described above, may help you to meet your audience’s expectations successfully. We’re going to proceed by explicitly connecting each section of the lab report to the scientific method, then explaining why and how you need to elaborate that section.

Although this handout takes each section in the order in which it should be presented in the final report, you may for practical reasons decide to compose sections in another order. For example, many writers find that composing their Methods and Results before the other sections helps to clarify their idea of the experiment or study as a whole. You might consider using each assignment to practice different approaches to drafting the report, to find the order that works best for you.

What should I do before drafting the lab report?

The best way to prepare to write the lab report is to make sure that you fully understand everything you need to about the experiment. Obviously, if you don’t quite know what went on during the lab, you’re going to find it difficult to explain the lab satisfactorily to someone else. To make sure you know enough to write the report, complete the following steps:

• What are we going to do in this lab? (That is, what’s the procedure?)
• Why are we going to do it that way?
• What are we hoping to learn from this experiment?
• Why would we benefit from this knowledge?
• Consult your lab supervisor as you perform the lab. If you don’t know how to answer one of the questions above, for example, your lab supervisor will probably be able to explain it to you (or, at least, help you figure it out).
• Plan the steps of the experiment carefully with your lab partners. The less you rush, the more likely it is that you’ll perform the experiment correctly and record your findings accurately. Also, take some time to think about the best way to organize the data before you have to start putting numbers down. If you can design a table to account for the data, that will tend to work much better than jotting results down hurriedly on a scrap piece of paper.
• Record the data carefully so you get them right. You won’t be able to trust your conclusions if you have the wrong data, and your readers will know you messed up if the other three people in your group have “97 degrees” and you have “87.”
• Consult with your lab partners about everything you do. Lab groups often make one of two mistakes: two people do all the work while two have a nice chat, or everybody works together until the group finishes gathering the raw data, then scrams outta there. Collaborate with your partners, even when the experiment is “over.” What trends did you observe? Was the hypothesis supported? Did you all get the same results? What kind of figure should you use to represent your findings? The whole group can work together to answer these questions.
• Consider your audience. You may believe that audience is a non-issue: it’s your lab TA, right? Well, yes—but again, think beyond the classroom. If you write with only your lab instructor in mind, you may omit material that is crucial to a complete understanding of your experiment, because you assume the instructor knows all that stuff already. As a result, you may receive a lower grade, since your TA won’t be sure that you understand all the principles at work. Try to write towards a student in the same course but a different lab section. That student will have a fair degree of scientific expertise but won’t know much about your experiment particularly. Alternatively, you could envision yourself five years from now, after the reading and lectures for this course have faded a bit. What would you remember, and what would you need explained more clearly (as a refresher)?

Once you’ve completed these steps as you perform the experiment, you’ll be in a good position to draft an effective lab report.

Introductions

How do i write a strong introduction.

For the purposes of this handout, we’ll consider the Introduction to contain four basic elements: the purpose, the scientific literature relevant to the subject, the hypothesis, and the reasons you believed your hypothesis viable. Let’s start by going through each element of the Introduction to clarify what it covers and why it’s important. Then we can formulate a logical organizational strategy for the section.

The inclusion of the purpose (sometimes called the objective) of the experiment often confuses writers. The biggest misconception is that the purpose is the same as the hypothesis. Not quite. We’ll get to hypotheses in a minute, but basically they provide some indication of what you expect the experiment to show. The purpose is broader, and deals more with what you expect to gain through the experiment. In a professional setting, the hypothesis might have something to do with how cells react to a certain kind of genetic manipulation, but the purpose of the experiment is to learn more about potential cancer treatments. Undergraduate reports don’t often have this wide-ranging a goal, but you should still try to maintain the distinction between your hypothesis and your purpose. In a solubility experiment, for example, your hypothesis might talk about the relationship between temperature and the rate of solubility, but the purpose is probably to learn more about some specific scientific principle underlying the process of solubility.

For starters, most people say that you should write out your working hypothesis before you perform the experiment or study. Many beginning science students neglect to do so and find themselves struggling to remember precisely which variables were involved in the process or in what way the researchers felt that they were related. Write your hypothesis down as you develop it—you’ll be glad you did.

As for the form a hypothesis should take, it’s best not to be too fancy or complicated; an inventive style isn’t nearly so important as clarity here. There’s nothing wrong with beginning your hypothesis with the phrase, “It was hypothesized that . . .” Be as specific as you can about the relationship between the different objects of your study. In other words, explain that when term A changes, term B changes in this particular way. Readers of scientific writing are rarely content with the idea that a relationship between two terms exists—they want to know what that relationship entails.

Not a hypothesis:

“It was hypothesized that there is a significant relationship between the temperature of a solvent and the rate at which a solute dissolves.”

Hypothesis:

“It was hypothesized that as the temperature of a solvent increases, the rate at which a solute will dissolve in that solvent increases.”

Put more technically, most hypotheses contain both an independent and a dependent variable. The independent variable is what you manipulate to test the reaction; the dependent variable is what changes as a result of your manipulation. In the example above, the independent variable is the temperature of the solvent, and the dependent variable is the rate of solubility. Be sure that your hypothesis includes both variables.

Justify your hypothesis

You need to do more than tell your readers what your hypothesis is; you also need to assure them that this hypothesis was reasonable, given the circumstances. In other words, use the Introduction to explain that you didn’t just pluck your hypothesis out of thin air. (If you did pluck it out of thin air, your problems with your report will probably extend beyond using the appropriate format.) If you posit that a particular relationship exists between the independent and the dependent variable, what led you to believe your “guess” might be supported by evidence?

Scientists often refer to this type of justification as “motivating” the hypothesis, in the sense that something propelled them to make that prediction. Often, motivation includes what we already know—or rather, what scientists generally accept as true (see “Background/previous research” below). But you can also motivate your hypothesis by relying on logic or on your own observations. If you’re trying to decide which solutes will dissolve more rapidly in a solvent at increased temperatures, you might remember that some solids are meant to dissolve in hot water (e.g., bouillon cubes) and some are used for a function precisely because they withstand higher temperatures (they make saucepans out of something). Or you can think about whether you’ve noticed sugar dissolving more rapidly in your glass of iced tea or in your cup of coffee. Even such basic, outside-the-lab observations can help you justify your hypothesis as reasonable.

Background/previous research

This part of the Introduction demonstrates to the reader your awareness of how you’re building on other scientists’ work. If you think of the scientific community as engaging in a series of conversations about various topics, then you’ll recognize that the relevant background material will alert the reader to which conversation you want to enter.

Generally speaking, authors writing journal articles use the background for slightly different purposes than do students completing assignments. Because readers of academic journals tend to be professionals in the field, authors explain the background in order to permit readers to evaluate the study’s pertinence for their own work. You, on the other hand, write toward a much narrower audience—your peers in the course or your lab instructor—and so you must demonstrate that you understand the context for the (presumably assigned) experiment or study you’ve completed. For example, if your professor has been talking about polarity during lectures, and you’re doing a solubility experiment, you might try to connect the polarity of a solid to its relative solubility in certain solvents. In any event, both professional researchers and undergraduates need to connect the background material overtly to their own work.

Organization of this section

Most of the time, writers begin by stating the purpose or objectives of their own work, which establishes for the reader’s benefit the “nature and scope of the problem investigated” (Day 1994). Once you have expressed your purpose, you should then find it easier to move from the general purpose, to relevant material on the subject, to your hypothesis. In abbreviated form, an Introduction section might look like this:

“The purpose of the experiment was to test conventional ideas about solubility in the laboratory [purpose] . . . According to Whitecoat and Labrat (1999), at higher temperatures the molecules of solvents move more quickly . . . We know from the class lecture that molecules moving at higher rates of speed collide with one another more often and thus break down more easily [background material/motivation] . . . Thus, it was hypothesized that as the temperature of a solvent increases, the rate at which a solute will dissolve in that solvent increases [hypothesis].”

Again—these are guidelines, not commandments. Some writers and readers prefer different structures for the Introduction. The one above merely illustrates a common approach to organizing material.

How do I write a strong Materials and Methods section?

As with any piece of writing, your Methods section will succeed only if it fulfills its readers’ expectations, so you need to be clear in your own mind about the purpose of this section. Let’s review the purpose as we described it above: in this section, you want to describe in detail how you tested the hypothesis you developed and also to clarify the rationale for your procedure. In science, it’s not sufficient merely to design and carry out an experiment. Ultimately, others must be able to verify your findings, so your experiment must be reproducible, to the extent that other researchers can follow the same procedure and obtain the same (or similar) results.

Here’s a real-world example of the importance of reproducibility. In 1989, physicists Stanley Pons and Martin Fleischman announced that they had discovered “cold fusion,” a way of producing excess heat and power without the nuclear radiation that accompanies “hot fusion.” Such a discovery could have great ramifications for the industrial production of energy, so these findings created a great deal of interest. When other scientists tried to duplicate the experiment, however, they didn’t achieve the same results, and as a result many wrote off the conclusions as unjustified (or worse, a hoax). To this day, the viability of cold fusion is debated within the scientific community, even though an increasing number of researchers believe it possible. So when you write your Methods section, keep in mind that you need to describe your experiment well enough to allow others to replicate it exactly.

With these goals in mind, let’s consider how to write an effective Methods section in terms of content, structure, and style.

Sometimes the hardest thing about writing this section isn’t what you should talk about, but what you shouldn’t talk about. Writers often want to include the results of their experiment, because they measured and recorded the results during the course of the experiment. But such data should be reserved for the Results section. In the Methods section, you can write that you recorded the results, or how you recorded the results (e.g., in a table), but you shouldn’t write what the results were—not yet. Here, you’re merely stating exactly how you went about testing your hypothesis. As you draft your Methods section, ask yourself the following questions:

• How much detail? Be precise in providing details, but stay relevant. Ask yourself, “Would it make any difference if this piece were a different size or made from a different material?” If not, you probably don’t need to get too specific. If so, you should give as many details as necessary to prevent this experiment from going awry if someone else tries to carry it out. Probably the most crucial detail is measurement; you should always quantify anything you can, such as time elapsed, temperature, mass, volume, etc.
• Rationale: Be sure that as you’re relating your actions during the experiment, you explain your rationale for the protocol you developed. If you capped a test tube immediately after adding a solute to a solvent, why did you do that? (That’s really two questions: why did you cap it, and why did you cap it immediately?) In a professional setting, writers provide their rationale as a way to explain their thinking to potential critics. On one hand, of course, that’s your motivation for talking about protocol, too. On the other hand, since in practical terms you’re also writing to your teacher (who’s seeking to evaluate how well you comprehend the principles of the experiment), explaining the rationale indicates that you understand the reasons for conducting the experiment in that way, and that you’re not just following orders. Critical thinking is crucial—robots don’t make good scientists.
• Control: Most experiments will include a control, which is a means of comparing experimental results. (Sometimes you’ll need to have more than one control, depending on the number of hypotheses you want to test.) The control is exactly the same as the other items you’re testing, except that you don’t manipulate the independent variable-the condition you’re altering to check the effect on the dependent variable. For example, if you’re testing solubility rates at increased temperatures, your control would be a solution that you didn’t heat at all; that way, you’ll see how quickly the solute dissolves “naturally” (i.e., without manipulation), and you’ll have a point of reference against which to compare the solutions you did heat.

Describe the control in the Methods section. Two things are especially important in writing about the control: identify the control as a control, and explain what you’re controlling for. Here is an example:

“As a control for the temperature change, we placed the same amount of solute in the same amount of solvent, and let the solution stand for five minutes without heating it.”

Structure and style

Organization is especially important in the Methods section of a lab report because readers must understand your experimental procedure completely. Many writers are surprised by the difficulty of conveying what they did during the experiment, since after all they’re only reporting an event, but it’s often tricky to present this information in a coherent way. There’s a fairly standard structure you can use to guide you, and following the conventions for style can help clarify your points.

• Subsections: Occasionally, researchers use subsections to report their procedure when the following circumstances apply: 1) if they’ve used a great many materials; 2) if the procedure is unusually complicated; 3) if they’ve developed a procedure that won’t be familiar to many of their readers. Because these conditions rarely apply to the experiments you’ll perform in class, most undergraduate lab reports won’t require you to use subsections. In fact, many guides to writing lab reports suggest that you try to limit your Methods section to a single paragraph.
• Narrative structure: Think of this section as telling a story about a group of people and the experiment they performed. Describe what you did in the order in which you did it. You may have heard the old joke centered on the line, “Disconnect the red wire, but only after disconnecting the green wire,” where the person reading the directions blows everything to kingdom come because the directions weren’t in order. We’re used to reading about events chronologically, and so your readers will generally understand what you did if you present that information in the same way. Also, since the Methods section does generally appear as a narrative (story), you want to avoid the “recipe” approach: “First, take a clean, dry 100 ml test tube from the rack. Next, add 50 ml of distilled water.” You should be reporting what did happen, not telling the reader how to perform the experiment: “50 ml of distilled water was poured into a clean, dry 100 ml test tube.” Hint: most of the time, the recipe approach comes from copying down the steps of the procedure from your lab manual, so you may want to draft the Methods section initially without consulting your manual. Later, of course, you can go back and fill in any part of the procedure you inadvertently overlooked.
• Past tense: Remember that you’re describing what happened, so you should use past tense to refer to everything you did during the experiment. Writers are often tempted to use the imperative (“Add 5 g of the solid to the solution”) because that’s how their lab manuals are worded; less frequently, they use present tense (“5 g of the solid are added to the solution”). Instead, remember that you’re talking about an event which happened at a particular time in the past, and which has already ended by the time you start writing, so simple past tense will be appropriate in this section (“5 g of the solid were added to the solution” or “We added 5 g of the solid to the solution”).
• Active: We heated the solution to 80°C. (The subject, “we,” performs the action, heating.)
• Passive: The solution was heated to 80°C. (The subject, “solution,” doesn’t do the heating–it is acted upon, not acting.)

Increasingly, especially in the social sciences, using first person and active voice is acceptable in scientific reports. Most readers find that this style of writing conveys information more clearly and concisely. This rhetorical choice thus brings two scientific values into conflict: objectivity versus clarity. Since the scientific community hasn’t reached a consensus about which style it prefers, you may want to ask your lab instructor.

How do I write a strong Results section?

Here’s a paradox for you. The Results section is often both the shortest (yay!) and most important (uh-oh!) part of your report. Your Materials and Methods section shows how you obtained the results, and your Discussion section explores the significance of the results, so clearly the Results section forms the backbone of the lab report. This section provides the most critical information about your experiment: the data that allow you to discuss how your hypothesis was or wasn’t supported. But it doesn’t provide anything else, which explains why this section is generally shorter than the others.

Before you write this section, look at all the data you collected to figure out what relates significantly to your hypothesis. You’ll want to highlight this material in your Results section. Resist the urge to include every bit of data you collected, since perhaps not all are relevant. Also, don’t try to draw conclusions about the results—save them for the Discussion section. In this section, you’re reporting facts. Nothing your readers can dispute should appear in the Results section.

Most Results sections feature three distinct parts: text, tables, and figures. Let’s consider each part one at a time.

This should be a short paragraph, generally just a few lines, that describes the results you obtained from your experiment. In a relatively simple experiment, one that doesn’t produce a lot of data for you to repeat, the text can represent the entire Results section. Don’t feel that you need to include lots of extraneous detail to compensate for a short (but effective) text; your readers appreciate discrimination more than your ability to recite facts. In a more complex experiment, you may want to use tables and/or figures to help guide your readers toward the most important information you gathered. In that event, you’ll need to refer to each table or figure directly, where appropriate:

“Table 1 lists the rates of solubility for each substance”

“Solubility increased as the temperature of the solution increased (see Figure 1).”

If you do use tables or figures, make sure that you don’t present the same material in both the text and the tables/figures, since in essence you’ll just repeat yourself, probably annoying your readers with the redundancy of your statements.

Feel free to describe trends that emerge as you examine the data. Although identifying trends requires some judgment on your part and so may not feel like factual reporting, no one can deny that these trends do exist, and so they properly belong in the Results section. Example:

“Heating the solution increased the rate of solubility of polar solids by 45% but had no effect on the rate of solubility in solutions containing non-polar solids.”

This point isn’t debatable—you’re just pointing out what the data show.

As in the Materials and Methods section, you want to refer to your data in the past tense, because the events you recorded have already occurred and have finished occurring. In the example above, note the use of “increased” and “had,” rather than “increases” and “has.” (You don’t know from your experiment that heating always increases the solubility of polar solids, but it did that time.)

You shouldn’t put information in the table that also appears in the text. You also shouldn’t use a table to present irrelevant data, just to show you did collect these data during the experiment. Tables are good for some purposes and situations, but not others, so whether and how you’ll use tables depends upon what you need them to accomplish.

Tables are useful ways to show variation in data, but not to present a great deal of unchanging measurements. If you’re dealing with a scientific phenomenon that occurs only within a certain range of temperatures, for example, you don’t need to use a table to show that the phenomenon didn’t occur at any of the other temperatures. How useful is this table?

As you can probably see, no solubility was observed until the trial temperature reached 50°C, a fact that the text part of the Results section could easily convey. The table could then be limited to what happened at 50°C and higher, thus better illustrating the differences in solubility rates when solubility did occur.

As a rule, try not to use a table to describe any experimental event you can cover in one sentence of text. Here’s an example of an unnecessary table from How to Write and Publish a Scientific Paper , by Robert A. Day:

As Day notes, all the information in this table can be summarized in one sentence: “S. griseus, S. coelicolor, S. everycolor, and S. rainbowenski grew under aerobic conditions, whereas S. nocolor and S. greenicus required anaerobic conditions.” Most readers won’t find the table clearer than that one sentence.

When you do have reason to tabulate material, pay attention to the clarity and readability of the format you use. Here are a few tips:

• Number your table. Then, when you refer to the table in the text, use that number to tell your readers which table they can review to clarify the material.
• Give your table a title. This title should be descriptive enough to communicate the contents of the table, but not so long that it becomes difficult to follow. The titles in the sample tables above are acceptable.
• Arrange your table so that readers read vertically, not horizontally. For the most part, this rule means that you should construct your table so that like elements read down, not across. Think about what you want your readers to compare, and put that information in the column (up and down) rather than in the row (across). Usually, the point of comparison will be the numerical data you collect, so especially make sure you have columns of numbers, not rows.Here’s an example of how drastically this decision affects the readability of your table (from A Short Guide to Writing about Chemistry , by Herbert Beall and John Trimbur). Look at this table, which presents the relevant data in horizontal rows:

It’s a little tough to see the trends that the author presumably wants to present in this table. Compare this table, in which the data appear vertically:

The second table shows how putting like elements in a vertical column makes for easier reading. In this case, the like elements are the measurements of length and height, over five trials–not, as in the first table, the length and height measurements for each trial.

• Make sure to include units of measurement in the tables. Readers might be able to guess that you measured something in millimeters, but don’t make them try.
• Don’t use vertical lines as part of the format for your table. This convention exists because journals prefer not to have to reproduce these lines because the tables then become more expensive to print. Even though it’s fairly unlikely that you’ll be sending your Biology 11 lab report to Science for publication, your readers still have this expectation. Consequently, if you use the table-drawing option in your word-processing software, choose the option that doesn’t rely on a “grid” format (which includes vertical lines).

How do I include figures in my report?

Although tables can be useful ways of showing trends in the results you obtained, figures (i.e., illustrations) can do an even better job of emphasizing such trends. Lab report writers often use graphic representations of the data they collected to provide their readers with a literal picture of how the experiment went.

When should you use a figure?

Remember the circumstances under which you don’t need a table: when you don’t have a great deal of data or when the data you have don’t vary a lot. Under the same conditions, you would probably forgo the figure as well, since the figure would be unlikely to provide your readers with an additional perspective. Scientists really don’t like their time wasted, so they tend not to respond favorably to redundancy.

If you’re trying to decide between using a table and creating a figure to present your material, consider the following a rule of thumb. The strength of a table lies in its ability to supply large amounts of exact data, whereas the strength of a figure is its dramatic illustration of important trends within the experiment. If you feel that your readers won’t get the full impact of the results you obtained just by looking at the numbers, then a figure might be appropriate.

Of course, an undergraduate class may expect you to create a figure for your lab experiment, if only to make sure that you can do so effectively. If this is the case, then don’t worry about whether to use figures or not—concentrate instead on how best to accomplish your task.

Figures can include maps, photographs, pen-and-ink drawings, flow charts, bar graphs, and section graphs (“pie charts”). But the most common figure by far, especially for undergraduates, is the line graph, so we’ll focus on that type in this handout.

At the undergraduate level, you can often draw and label your graphs by hand, provided that the result is clear, legible, and drawn to scale. Computer technology has, however, made creating line graphs a lot easier. Most word-processing software has a number of functions for transferring data into graph form; many scientists have found Microsoft Excel, for example, a helpful tool in graphing results. If you plan on pursuing a career in the sciences, it may be well worth your while to learn to use a similar program.

Computers can’t, however, decide for you how your graph really works; you have to know how to design your graph to meet your readers’ expectations. Here are some of these expectations:

• Keep it as simple as possible. You may be tempted to signal the complexity of the information you gathered by trying to design a graph that accounts for that complexity. But remember the purpose of your graph: to dramatize your results in a manner that’s easy to see and grasp. Try not to make the reader stare at the graph for a half hour to find the important line among the mass of other lines. For maximum effectiveness, limit yourself to three to five lines per graph; if you have more data to demonstrate, use a set of graphs to account for it, rather than trying to cram it all into a single figure.
• Plot the independent variable on the horizontal (x) axis and the dependent variable on the vertical (y) axis. Remember that the independent variable is the condition that you manipulated during the experiment and the dependent variable is the condition that you measured to see if it changed along with the independent variable. Placing the variables along their respective axes is mostly just a convention, but since your readers are accustomed to viewing graphs in this way, you’re better off not challenging the convention in your report.
• Label each axis carefully, and be especially careful to include units of measure. You need to make sure that your readers understand perfectly well what your graph indicates.
• Number and title your graphs. As with tables, the title of the graph should be informative but concise, and you should refer to your graph by number in the text (e.g., “Figure 1 shows the increase in the solubility rate as a function of temperature”).
• Many editors of professional scientific journals prefer that writers distinguish the lines in their graphs by attaching a symbol to them, usually a geometric shape (triangle, square, etc.), and using that symbol throughout the curve of the line. Generally, readers have a hard time distinguishing dotted lines from dot-dash lines from straight lines, so you should consider staying away from this system. Editors don’t usually like different-colored lines within a graph because colors are difficult and expensive to reproduce; colors may, however, be great for your purposes, as long as you’re not planning to submit your paper to Nature. Use your discretion—try to employ whichever technique dramatizes the results most effectively.
• Try to gather data at regular intervals, so the plot points on your graph aren’t too far apart. You can’t be sure of the arc you should draw between the plot points if the points are located at the far corners of the graph; over a fifteen-minute interval, perhaps the change occurred in the first or last thirty seconds of that period (in which case your straight-line connection between the points is misleading).
• If you’re worried that you didn’t collect data at sufficiently regular intervals during your experiment, go ahead and connect the points with a straight line, but you may want to examine this problem as part of your Discussion section.
• Make your graph large enough so that everything is legible and clearly demarcated, but not so large that it either overwhelms the rest of the Results section or provides a far greater range than you need to illustrate your point. If, for example, the seedlings of your plant grew only 15 mm during the trial, you don’t need to construct a graph that accounts for 100 mm of growth. The lines in your graph should more or less fill the space created by the axes; if you see that your data is confined to the lower left portion of the graph, you should probably re-adjust your scale.
• If you create a set of graphs, make them the same size and format, including all the verbal and visual codes (captions, symbols, scale, etc.). You want to be as consistent as possible in your illustrations, so that your readers can easily make the comparisons you’re trying to get them to see.

How do I write a strong Discussion section?

The discussion section is probably the least formalized part of the report, in that you can’t really apply the same structure to every type of experiment. In simple terms, here you tell your readers what to make of the Results you obtained. If you have done the Results part well, your readers should already recognize the trends in the data and have a fairly clear idea of whether your hypothesis was supported. Because the Results can seem so self-explanatory, many students find it difficult to know what material to add in this last section.

Basically, the Discussion contains several parts, in no particular order, but roughly moving from specific (i.e., related to your experiment only) to general (how your findings fit in the larger scientific community). In this section, you will, as a rule, need to:

Explain whether the data support your hypothesis

• Acknowledge any anomalous data or deviations from what you expected

Derive conclusions, based on your findings, about the process you’re studying

• Relate your findings to earlier work in the same area (if you can)

Explore the theoretical and/or practical implications of your findings

Let’s look at some dos and don’ts for each of these objectives.

This statement is usually a good way to begin the Discussion, since you can’t effectively speak about the larger scientific value of your study until you’ve figured out the particulars of this experiment. You might begin this part of the Discussion by explicitly stating the relationships or correlations your data indicate between the independent and dependent variables. Then you can show more clearly why you believe your hypothesis was or was not supported. For example, if you tested solubility at various temperatures, you could start this section by noting that the rates of solubility increased as the temperature increased. If your initial hypothesis surmised that temperature change would not affect solubility, you would then say something like,

“The hypothesis that temperature change would not affect solubility was not supported by the data.”

Note: Students tend to view labs as practical tests of undeniable scientific truths. As a result, you may want to say that the hypothesis was “proved” or “disproved” or that it was “correct” or “incorrect.” These terms, however, reflect a degree of certainty that you as a scientist aren’t supposed to have. Remember, you’re testing a theory with a procedure that lasts only a few hours and relies on only a few trials, which severely compromises your ability to be sure about the “truth” you see. Words like “supported,” “indicated,” and “suggested” are more acceptable ways to evaluate your hypothesis.

Also, recognize that saying whether the data supported your hypothesis or not involves making a claim to be defended. As such, you need to show the readers that this claim is warranted by the evidence. Make sure that you’re very explicit about the relationship between the evidence and the conclusions you draw from it. This process is difficult for many writers because we don’t often justify conclusions in our regular lives. For example, you might nudge your friend at a party and whisper, “That guy’s drunk,” and once your friend lays eyes on the person in question, she might readily agree. In a scientific paper, by contrast, you would need to defend your claim more thoroughly by pointing to data such as slurred words, unsteady gait, and the lampshade-as-hat. In addition to pointing out these details, you would also need to show how (according to previous studies) these signs are consistent with inebriation, especially if they occur in conjunction with one another. To put it another way, tell your readers exactly how you got from point A (was the hypothesis supported?) to point B (yes/no).

Acknowledge any anomalous data, or deviations from what you expected

You need to take these exceptions and divergences into account, so that you qualify your conclusions sufficiently. For obvious reasons, your readers will doubt your authority if you (deliberately or inadvertently) overlook a key piece of data that doesn’t square with your perspective on what occurred. In a more philosophical sense, once you’ve ignored evidence that contradicts your claims, you’ve departed from the scientific method. The urge to “tidy up” the experiment is often strong, but if you give in to it you’re no longer performing good science.

Sometimes after you’ve performed a study or experiment, you realize that some part of the methods you used to test your hypothesis was flawed. In that case, it’s OK to suggest that if you had the chance to conduct your test again, you might change the design in this or that specific way in order to avoid such and such a problem. The key to making this approach work, though, is to be very precise about the weakness in your experiment, why and how you think that weakness might have affected your data, and how you would alter your protocol to eliminate—or limit the effects of—that weakness. Often, inexperienced researchers and writers feel the need to account for “wrong” data (remember, there’s no such animal), and so they speculate wildly about what might have screwed things up. These speculations include such factors as the unusually hot temperature in the room, or the possibility that their lab partners read the meters wrong, or the potentially defective equipment. These explanations are what scientists call “cop-outs,” or “lame”; don’t indicate that the experiment had a weakness unless you’re fairly certain that a) it really occurred and b) you can explain reasonably well how that weakness affected your results.

If, for example, your hypothesis dealt with the changes in solubility at different temperatures, then try to figure out what you can rationally say about the process of solubility more generally. If you’re doing an undergraduate lab, chances are that the lab will connect in some way to the material you’ve been covering either in lecture or in your reading, so you might choose to return to these resources as a way to help you think clearly about the process as a whole.

This part of the Discussion section is another place where you need to make sure that you’re not overreaching. Again, nothing you’ve found in one study would remotely allow you to claim that you now “know” something, or that something isn’t “true,” or that your experiment “confirmed” some principle or other. Hesitate before you go out on a limb—it’s dangerous! Use less absolutely conclusive language, including such words as “suggest,” “indicate,” “correspond,” “possibly,” “challenge,” etc.

Relate your findings to previous work in the field (if possible)

We’ve been talking about how to show that you belong in a particular community (such as biologists or anthropologists) by writing within conventions that they recognize and accept. Another is to try to identify a conversation going on among members of that community, and use your work to contribute to that conversation. In a larger philosophical sense, scientists can’t fully understand the value of their research unless they have some sense of the context that provoked and nourished it. That is, you have to recognize what’s new about your project (potentially, anyway) and how it benefits the wider body of scientific knowledge. On a more pragmatic level, especially for undergraduates, connecting your lab work to previous research will demonstrate to the TA that you see the big picture. You have an opportunity, in the Discussion section, to distinguish yourself from the students in your class who aren’t thinking beyond the barest facts of the study. Capitalize on this opportunity by putting your own work in context.

If you’re just beginning to work in the natural sciences (as a first-year biology or chemistry student, say), most likely the work you’ll be doing has already been performed and re-performed to a satisfactory degree. Hence, you could probably point to a similar experiment or study and compare/contrast your results and conclusions. More advanced work may deal with an issue that is somewhat less “resolved,” and so previous research may take the form of an ongoing debate, and you can use your own work to weigh in on that debate. If, for example, researchers are hotly disputing the value of herbal remedies for the common cold, and the results of your study suggest that Echinacea diminishes the symptoms but not the actual presence of the cold, then you might want to take some time in the Discussion section to recapitulate the specifics of the dispute as it relates to Echinacea as an herbal remedy. (Consider that you have probably already written in the Introduction about this debate as background research.)

This information is often the best way to end your Discussion (and, for all intents and purposes, the report). In argumentative writing generally, you want to use your closing words to convey the main point of your writing. This main point can be primarily theoretical (“Now that you understand this information, you’re in a better position to understand this larger issue”) or primarily practical (“You can use this information to take such and such an action”). In either case, the concluding statements help the reader to comprehend the significance of your project and your decision to write about it.

Since a lab report is argumentative—after all, you’re investigating a claim, and judging the legitimacy of that claim by generating and collecting evidence—it’s often a good idea to end your report with the same technique for establishing your main point. If you want to go the theoretical route, you might talk about the consequences your study has for the field or phenomenon you’re investigating. To return to the examples regarding solubility, you could end by reflecting on what your work on solubility as a function of temperature tells us (potentially) about solubility in general. (Some folks consider this type of exploration “pure” as opposed to “applied” science, although these labels can be problematic.) If you want to go the practical route, you could end by speculating about the medical, institutional, or commercial implications of your findings—in other words, answer the question, “What can this study help people to do?” In either case, you’re going to make your readers’ experience more satisfying, by helping them see why they spent their time learning what you had to teach them.

Works consulted

We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.

American Psychological Association. 2010. Publication Manual of the American Psychological Association . 6th ed. Washington, DC: American Psychological Association.

Beall, Herbert, and John Trimbur. 2001. A Short Guide to Writing About Chemistry , 2nd ed. New York: Longman.

Blum, Deborah, and Mary Knudson. 1997. A Field Guide for Science Writers: The Official Guide of the National Association of Science Writers . New York: Oxford University Press.

Booth, Wayne C., Gregory G. Colomb, Joseph M. Williams, Joseph Bizup, and William T. FitzGerald. 2016. The Craft of Research , 4th ed. Chicago: University of Chicago Press.

Briscoe, Mary Helen. 1996. Preparing Scientific Illustrations: A Guide to Better Posters, Presentations, and Publications , 2nd ed. New York: Springer-Verlag.

Council of Science Editors. 2014. Scientific Style and Format: The CSE Manual for Authors, Editors, and Publishers , 8th ed. Chicago & London: University of Chicago Press.

Davis, Martha. 2012. Scientific Papers and Presentations , 3rd ed. London: Academic Press.

Day, Robert A. 1994. How to Write and Publish a Scientific Paper , 4th ed. Phoenix: Oryx Press.

Porush, David. 1995. A Short Guide to Writing About Science . New York: Longman.

Williams, Joseph, and Joseph Bizup. 2017. Style: Lessons in Clarity and Grace , 12th ed. Boston: Pearson.

You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill

Make a Gift

• Subject Guides

Academic writing: a practical guide

• Academic writing
• The writing process
• Academic writing style
• Structure & cohesion
• Criticality in academic writing
• Working with evidence
• Referencing
• Assessment & feedback
• Dissertations
• Reflective writing
• Examination writing
• Academic posters
• Feedback on Structure and Organisation
• Feedback on Argument, Analysis, and Critical Thinking
• Feedback on Writing Style and Clarity
• Feedback on Referencing and Research
• Feedback on Presentation and Proofreading

Objective, evidence-based writing commonly used in the sciences and some social science subjects.

Introduction to reports

Reports are found within many subjects, particularly sciences and some social sciences. They present factual-based information for a specified audience, with each academic discipline area having its own report types (many of which are based on real-world reports). 

This guide explores what an academic report is as a concept and offers practical advice about the completion of academic reports:

Reports: a Conceptual and Practical Guide [interactive slides]  |  Reports: a Conceptual and Practical Guide [Google Doc]

Features of reports

• Reports present and (usually) critically analyse data and other factual evidence.
• There are different types of reports , which each have a specific purpose.
• There is often a specific structure that must be followed - see our general structure advice and guidance for each report type.
• The writing style is concise and objective - for more detail, see our academic writing style advice.

The report writing process

Writing a good report isn't just about the final product - much of the thinking and hard work is done before you start writing.

Before your first report, work through the introductory guide to reports above to get an idea of what's expected of you:  Reports: a Conceptual and Practical Guide [interactive tutorial]

Read the assessment instructions carefully. Which type of report is it? Is there an expected structure? Do you need to analyse data? What's the word count? When's the deadline?

Look at the  assignment writing process  and think about how you'll plan your approach to your report.

Make a schedule: how much time do you need to research, think, plan, draft, write and edit your report? Add in some extra time for a buffer.

Follow the steps in the writing process to prepare and write your report. Try to stick to your schedule.

Check and proofread your report carefully - check your citations and references too! 

Submit your report. Maybe celebrate with some cake?

Read your feedback  carefully. How can you use it to improve your next report? 

For more detail, see our dedicated advice pages:

Note taking for synthesising information

In many types of academic writing, you need to compare and synthesise information from numerous sources. This process much is quicker and easier using an effective note-taking technique.

Grid notes  is a useful note taking technique to synthesise information. You collect information under specific headings in a grid or table, which helps you to:

• pull all your notes together in one place.
• focus on finding just the information you need in sources.
• identify patterns in source information.
• plan structure and write.

Find out more:

Grid notes [YouTube]  | Grid notes [Google Doc]

More advice about other note-taking methods:

Using evidence in reports

Sources of evidence.

Reports are based on factual evidence and data, found in sources such as:

• your own research findings (quantitative or qualitative)
• findings from research papers (quantitative or qualitative)
• published governmental or organisational datasets
• reports from companies or organisations
• business case studies

Tips on finding appropriate sources of evidence for your reports:

Reading academic journals

Writing a report usually requires reading lots of journal papers. This can seem like a massive task, but you usually don't need to read every word of a paper to get the information you need!

Find tips and strategies to read papers effectively:

Using evidence critically

It's not enough to describe or summarise the evidence - to access higher grades you'll also need to critically analyse it. What does the evidence mean in relation to your overall point or argument?

There are many ways that you could use evidence critically, such as:

• evaluate or justify methodological choices
• consider how your findings fit into previous research
• compare findings, models or frameworks
• evaluate different solutions or applications and select the most effective one
• make evidence-based recommendations

For more advice, see our dedicated criticality resources:

Research reports

Research or experimental reports present and discuss the outcomes of your research: what did you do , what did you find out , and what does it mean?

They're very common in science subjects and sometimes used in Education, Management or other subjects.

Research reports usually follow a set structure:

• introduction

Writing a research report

This tutorial introduces what's expected in each section, with advice and examples:

Writing a research report [interactive tutorial]  |  Writing a research report [Google Doc]

Many dissertations also follow this structure, so these tips also apply to research reports:

Example research reports

Example research reports may be available on your module VLE sites or from your tutors.

Research-based journal papers are also usually based on the same principles, so reading papers from your field is also a good way to see what's expected. Note that the referencing style used by the journal might be different to your department's referencing style!

This ecology paper is a well-structured example of a research paper:

Other support for report writing

Online resources.

The general writing pages of this site offer guidance that can be applied to all types of writing, including reports. Also check your department guidance and VLE sites for tailored resources.

Other useful resources for report writing:

Appointments and workshops 

As well as advice within your department, you can access central writing and skills support:

Have questions about planning or interpreting quantitative data analysis? You can book a statistics appointment with the Maths Skills Centre or explore the workshops and online resources:

• << Previous: Essays
• Next: Dissertations >>
• Last Updated: Jun 4, 2024 10:44 AM
• URL: https://subjectguides.york.ac.uk/academic-writing

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

• Knowledge Base
• Methodology

Research Design | Step-by-Step Guide with Examples

Published on 5 May 2022 by Shona McCombes . Revised on 20 March 2023.

A research design is a strategy for answering your research question  using empirical data. Creating a research design means making decisions about:

• Your overall aims and approach
• The type of research design you’ll use
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research aims and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, frequently asked questions.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities – start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

Prevent plagiarism, run a free check.

Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types. Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships, while descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends, and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analysing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study – plants, animals, organisations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region, or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalise your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study, your aim is to deeply understand a specific context, not to generalise to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question.

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviours, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews.

Observation methods

Observations allow you to collect data unobtrusively, observing characteristics, behaviours, or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected – for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are reliable and valid.

Operationalisation

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalisation means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in – for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced , while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method, you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample – by mail, online, by phone, or in person?

If you’re using a probability sampling method, it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method, how will you avoid bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organising and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymise and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well organised will save time when it comes to analysing them. It can also help other researchers validate and add to your findings.

On their own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyse the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarise your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarise your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analysing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
• If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

McCombes, S. (2023, March 20). Research Design | Step-by-Step Guide with Examples. Scribbr. Retrieved 7 June 2024, from https://www.scribbr.co.uk/research-methods/research-design/

Is this article helpful?

Shona McCombes

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• J Korean Med Sci
• v.37(16); 2022 Apr 25

A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

• EXAMPLE 1. Descriptive research question (quantitative research)
• - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
• “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
• RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
• EXAMPLE 2. Relationship research question (quantitative research)
• - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
• “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
• Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
• EXAMPLE 3. Comparative research question (quantitative research)
• - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
• “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
• RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
• STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
• EXAMPLE 4. Exploratory research question (qualitative research)
• - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
• “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
• EXAMPLE 5. Relationship research question (quantitative research)
• - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
• “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

• EXAMPLE 1. Working hypothesis (quantitative research)
• - A hypothesis that is initially accepted for further research to produce a feasible theory
• “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
• “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
• EXAMPLE 2. Exploratory hypothesis (qualitative research)
• - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
• “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
• “Conclusion
• Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
• EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
• “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
• Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
• EXAMPLE 4. Statistical hypothesis (quantitative research)
• - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
• “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
• “Statistical Analysis
• ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

• EXAMPLE 1. Background, hypotheses, and aims are provided
• “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
• “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
• “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
• EXAMPLE 2. Background, hypotheses, and aims are provided
• “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
• “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
• EXAMPLE 3. Background, aim, and hypothesis are provided
• “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
• “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
• “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Methodology: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ.

Community Blog

Keep up-to-date on postgraduate related issues with our quick reads written by students, postdocs, professors and industry leaders.

Types of Research – Explained with Examples

• By DiscoverPhDs
• October 2, 2020

Types of Research

Research is about using established methods to investigate a problem or question in detail with the aim of generating new knowledge about it.

It is a vital tool for scientific advancement because it allows researchers to prove or refute hypotheses based on clearly defined parameters, environments and assumptions. Due to this, it enables us to confidently contribute to knowledge as it allows research to be verified and replicated.

Knowing the types of research and what each of them focuses on will allow you to better plan your project, utilises the most appropriate methodologies and techniques and better communicate your findings to other researchers and supervisors.

Classification of Types of Research

There are various types of research that are classified according to their objective, depth of study, analysed data, time required to study the phenomenon and other factors. It’s important to note that a research project will not be limited to one type of research, but will likely use several.

According to its Purpose

Theoretical research.

Theoretical research, also referred to as pure or basic research, focuses on generating knowledge , regardless of its practical application. Here, data collection is used to generate new general concepts for a better understanding of a particular field or to answer a theoretical research question.

Results of this kind are usually oriented towards the formulation of theories and are usually based on documentary analysis, the development of mathematical formulas and the reflection of high-level researchers.

Applied Research

Here, the goal is to find strategies that can be used to address a specific research problem. Applied research draws on theory to generate practical scientific knowledge, and its use is very common in STEM fields such as engineering, computer science and medicine.

This type of research is subdivided into two types:

• Technological applied research : looks towards improving efficiency in a particular productive sector through the improvement of processes or machinery related to said productive processes.
• Scientific applied research : has predictive purposes. Through this type of research design, we can measure certain variables to predict behaviours useful to the goods and services sector, such as consumption patterns and viability of commercial projects.

According to your Depth of Scope

Exploratory research.

Exploratory research is used for the preliminary investigation of a subject that is not yet well understood or sufficiently researched. It serves to establish a frame of reference and a hypothesis from which an in-depth study can be developed that will enable conclusive results to be generated.

Because exploratory research is based on the study of little-studied phenomena, it relies less on theory and more on the collection of data to identify patterns that explain these phenomena.

Descriptive Research

The primary objective of descriptive research is to define the characteristics of a particular phenomenon without necessarily investigating the causes that produce it.

In this type of research, the researcher must take particular care not to intervene in the observed object or phenomenon, as its behaviour may change if an external factor is involved.

Explanatory Research

Explanatory research is the most common type of research method and is responsible for establishing cause-and-effect relationships that allow generalisations to be extended to similar realities. It is closely related to descriptive research, although it provides additional information about the observed object and its interactions with the environment.

Correlational Research

The purpose of this type of scientific research is to identify the relationship between two or more variables. A correlational study aims to determine whether a variable changes, how much the other elements of the observed system change.

According to the Type of Data Used

Qualitative research.

Qualitative methods are often used in the social sciences to collect, compare and interpret information, has a linguistic-semiotic basis and is used in techniques such as discourse analysis, interviews, surveys, records and participant observations.

In order to use statistical methods to validate their results, the observations collected must be evaluated numerically. Qualitative research, however, tends to be subjective, since not all data can be fully controlled. Therefore, this type of research design is better suited to extracting meaning from an event or phenomenon (the ‘why’) than its cause (the ‘how’).

Quantitative Research

Quantitative research study delves into a phenomena through quantitative data collection and using mathematical, statistical and computer-aided tools to measure them . This allows generalised conclusions to be projected over time.

According to the Degree of Manipulation of Variables

Experimental research.

It is about designing or replicating a phenomenon whose variables are manipulated under strictly controlled conditions in order to identify or discover its effect on another independent variable or object. The phenomenon to be studied is measured through study and control groups, and according to the guidelines of the scientific method.

Non-Experimental Research

Also known as an observational study, it focuses on the analysis of a phenomenon in its natural context. As such, the researcher does not intervene directly, but limits their involvement to measuring the variables required for the study. Due to its observational nature, it is often used in descriptive research.

Quasi-Experimental Research

It controls only some variables of the phenomenon under investigation and is therefore not entirely experimental. In this case, the study and the focus group cannot be randomly selected, but are chosen from existing groups or populations . This is to ensure the collected data is relevant and that the knowledge, perspectives and opinions of the population can be incorporated into the study.

According to the Type of Inference

Deductive investigation.

In this type of research, reality is explained by general laws that point to certain conclusions; conclusions are expected to be part of the premise of the research problem and considered correct if the premise is valid and the inductive method is applied correctly.

Inductive Research

In this type of research, knowledge is generated from an observation to achieve a generalisation. It is based on the collection of specific data to develop new theories.

Hypothetical-Deductive Investigation

It is based on observing reality to make a hypothesis, then use deduction to obtain a conclusion and finally verify or reject it through experience.

According to the Time in Which it is Carried Out

Longitudinal study (also referred to as diachronic research).

It is the monitoring of the same event, individual or group over a defined period of time. It aims to track changes in a number of variables and see how they evolve over time. It is often used in medical, psychological and social areas .

Cross-Sectional Study (also referred to as Synchronous Research)

Cross-sectional research design is used to observe phenomena, an individual or a group of research subjects at a given time.

According to The Sources of Information

Primary research.

This fundamental research type is defined by the fact that the data is collected directly from the source, that is, it consists of primary, first-hand information.

Secondary research

Unlike primary research, secondary research is developed with information from secondary sources, which are generally based on scientific literature and other documents compiled by another researcher.

According to How the Data is Obtained

Documentary (cabinet).

Documentary research, or secondary sources, is based on a systematic review of existing sources of information on a particular subject. This type of scientific research is commonly used when undertaking literature reviews or producing a case study.

Field research study involves the direct collection of information at the location where the observed phenomenon occurs.

From Laboratory

Laboratory research is carried out in a controlled environment in order to isolate a dependent variable and establish its relationship with other variables through scientific methods.

Mixed-Method: Documentary, Field and/or Laboratory

Mixed research methodologies combine results from both secondary (documentary) sources and primary sources through field or laboratory research.

Find out the differences between a Literature Review and an Annotated Bibliography, whey they should be used and how to write them.

How should you spend your first week as a PhD student? Here’s are 7 steps to help you get started on your journey.

Need to write a list of abbreviations for a thesis or dissertation? Read our post to find out where they go, what to include and how to format them.

Join thousands of other students and stay up to date with the latest PhD programmes, funding opportunities and advice.

Browse PhDs Now

This article will answer common questions about the PhD synopsis, give guidance on how to write one, and provide my thoughts on samples.

The title page of your dissertation or thesis conveys all the essential details about your project. This guide helps you format it in the correct way.

Chris is a third (and final) year PhD student at Ulster University. His project aims to develop a novel method of delivering antibiofilm compounds directly to an infected wound bed in patients.

Dr Grayson gained her PhD in Mechanical Engineering from Cornell University in 2016. She now works in industry as an Applications Portfolio Manager and is a STEM Speaker and Advocate.

Join Thousands of Students

A Guide To The Top 14 Types Of Reports With Examples Of When To Use Them

Table of Contents

1) What Is The Report Definition?

2) Top 14 Types Of Reports

3) What Does A Report Look Like?

4) What To Look For In A Reporting Tool

Businesses have been producing reports forever. No matter what role or industry you work in, chances are that you have been faced with the task of generating a tedious report to show your progress or performance.

While reporting has been a common practice for many decades, the business world keeps evolving, and with more competitive industries, the need to generate fast and accurate reports becomes critical. This presents a problem for many modern organizations today, as building reports can take from hours to days. In fact, a survey about management reports performed by Deloitte says that 50% of managers are unsatisfied with the speed of delivery and the quality of the reports they receive. 

With this issue in mind, several BI tools have been developed to assist businesses in generating interactive reports with just a few clicks, enhancing the way companies make critical decisions and service insights from their most valuable data.

But, with so many types of reports used daily, how can you know when to use them effectively? How can you push yourself ahead of the pack with the power of information? Here, we will explore the 14 most common types of reports in business and provide some examples of when to use them to your brand-boosting advantage. In addition, we will see how online dashboards have overthrown the static nature of classic reports and given way to a much faster, more interactive way of working with data.

Let’s get started with a brief report definition.

What Is The Report Definition?

A report is a document that presents relevant business information in an organized and understandable format. Each report is aimed at a specific audience and business purpose, and it summarizes the development of different activities based on goals and objectives.  

That said, there are various types of reports that can be used for different purposes. Whether you want to track the progress of your strategies or stay compliant with financial laws, there is a different report for each task. To help you identify when to use them, we will cover the top 14 most common report formats used for businesses today. 

What Are The Different Types Of Reports?

1. Informational Reports 

The first in our list of reporting types is informational reports. As their name suggests, this report type aims to give factual insights about a specific topic. This can include performance reports, expense reports, and justification reports, among others. A differentiating characteristic of these reports is their objectivity; they are only meant to inform but not propose solutions or hypotheses. Common informational reports examples are for performance tracking, such as annual, monthly, or weekly reports . 

2. Analytical Reports 

This report type contains a mix of useful information to facilitate the decision-making process through a mix of qualitative and quantitative insights as well as real-time and historical insights. Unlike informational reports that purely inform users about a topic, this report type also aims to provide recommendations about the next steps and help with problem-solving. With this information in hand, businesses can build strategies based on analytical evidence and not simple intuition. With the use of the right BI reporting tool , businesses can generate various types of analytical reports that include accurate forecasts via predictive analytics technologies. Let's look at it with an analytical report example.

**click to enlarge**

The example above is the perfect representation of how analytical reports can boost a business’s performance. By getting detailed information such as sales opportunities, a probability rate, as well as an accurate pipeline value forecast based on historical data, sales teams can prepare their strategies in advance, tackle any inefficiencies, and make informed decisions for increased efficiency. 

3. Operational Reports 

These reports track every pertinent detail of the company's operational tasks, such as its production processes. They are typically short-term reports as they aim to paint a picture of the present. Businesses use this type of report to spot any issues and define their solutions or to identify improvement opportunities to optimize their operational efficiency. Operational reports are commonly used in manufacturing, logistics, and retail as they help keep track of inventory, production, and costs, among others. 

4. Product Reports

As its name suggests, this report type is used to monitor several aspects related to product development. Businesses often use them to track which of their products or subscriptions are selling the most within a given time period, calculate inventories, or see what kind of product the client values the most. Another common use case of these reports is to research the implementation of new products or develop existing ones. Let’s see it in more detail with a visual example. 

The image above is a product report that shows valuable insights regarding usage intention, purchase intention, willingness to pay, and more. In this case, the report is based on the answers from a survey that aimed to understand how the target customer would receive a new product. Getting this level of insights through this report type is very useful for businesses as it allows them to make smart investments when it comes to new products as well as set realistic pricing based on their client’s willingness to pay. 

5. Industry Reports 

Next in our list of the most common kinds of reports, we have industry-specific reports. Typically, these reports provide an overview of a particular industry, market, or sector with definitions, key trends, leading companies, and industry size, among others. They are particularly useful for businesses that want to enter a specific industry and want to learn how competitive it is or for companies who are looking to set performance benchmarks based on average industry values. 

6. Department Reports

These reports are specific to each department or business function. They serve as a communication tool between managers and team members who must stay connected and work together for common goals. Whether it is the sales department, customer service, logistics, or finances, this specific report type helps track and optimize strategies on a deeper level. Let’s look at it with an example of a team performance report . 

The image above is a department report created with an online data analysis tool , and it tracks the performance of a support team. This insightful report displays relevant metrics such as the top-performing agents, net promoter score, and first contact resolution rate, among others. Having this information in hand not only helps each team member to keep track of their individual progress but also allows managers to understand who needs more training and who is performing at their best. 

7. Progress Reports

From the brunch of informational reports, progress reports provide critical information about the status of a project. These reports can be produced on a daily, weekly, or monthly basis by employees or managers to track performance and fine-tune tasks for the better development of the project. Progress reports are often used as visual materials to support meetings and discussions. A good example is a KPI scorecard . 

8. Internal Reports

A type of report that encompasses many others on this list, internal reports refer to any type of report that is used internally in a business. They convey information between team members and departments to keep communication flowing regarding goals and business objectives. 

As mentioned above, internal reports are useful communication tools to keep every relevant person in the organization informed and engaged. This healthcare report aims to do just that. By providing insights into the performance of different departments and areas of a hospital, such as in and outpatients, average waiting times, treatment costs, and more, healthcare managers can allocate resources and plan the schedule accurately, as well as monitor any changes or issues in real-time. 

9. External Reports

Although most of the reports types listed here are used for internal purposes, not all reporting is meant to be used behind closed doors. External reports are created to share information with external stakeholders such as clients or investors for budget or progress accountability, as well as to governmental bodies to stay compliant with the law requirements.

The image above is the perfect example of an external client report from an IT project. This insightful report provides a visual overview of every relevant aspect of the project's development. From deadlines, budget usage, completion stage, and task breakdown, clients can be fully informed and involved in the project. 

10. Vertical & Lateral Reports 

Next, in our rundown of types of reports, we have vertical and lateral reports. This reporting type refers to the direction in which a report travels. A vertical report is meant to go upward or downward the hierarchy, for example, a management report. A lateral report assists in organization and communication between groups that are at the same level of the hierarchy, such as the financial and marketing departments.

11. Research Reports

Without a doubt, one of the most vital reporting types for any modern business is centered on research. Being able to collect, collate, and drill down into insights based on key pockets of your customer base or industry will give you the tools to drive innovation while meeting your audience’s needs head-on.

The image above is a market research analytics report example for customer demographics. It serves up a balanced blend of metrics that will empower you to boost engagement as well as retention rates. Here, you can drill down into your audience’s behaviors, interests, gender, educational levels, and tech adoption life cycles with a simple glance.

What’s particularly striking about this dashboard is the fact that you can explore key trends in brand innovation with ease, gaining a working insight into how your audience perceives your business. This invaluable type of report will help you get under the skin of your consumers, driving growth and loyalty in the process.

12. Strategic Reports

Strategy is a vital component of every business, big or small. Strategic analytics tools are perhaps the broadest and most universal of all the different types of business reports imaginable.

These particular tools exist to help you understand, meet, and exceed your most pressing organizational goals consistently by serving up top-level metrics on a variety of initiatives or functions.

By working with strategic-style tools, you will:

• Improve internal motivation and engagement
• Refine your plans and strategies for the best possible return on investment (ROI)
• Enhance internal communication and optimize the way your various departments run
• Create more room for innovation and creative thinking

13. Project Reports

Projects are key to keeping a business moving in the right direction while keeping innovation and evolution at the forefront of every plan, communication, or campaign. But without the right management tools, a potentially groundbreaking project can become a resource-sapping disaster.

A project management report serves as a summary of a particular project's status and its various components. It's a visual tool that you can share with partners, colleagues, clients, and stakeholders to showcase your project's progress at multiple stages. Let’s look at our example and dig a little deeper.

To ensure consistent success across the board, the kinds of reports you must work with are based on project management. 

Our example is a project management dashboard equipped with a melting pot of metrics designed to improve the decision-making process while keeping every facet of your company’s most important initiatives under control. Here, you can spot pivotal trends based on costs, task statuses, margins, costs, and overall project revenue. With this cohesive visual information at your fingertips, not only can you ensure the smooth end-to-end running of any key project, but you can also drive increased operational efficiency as you move through every significant milestone.

14. Statutory Reports

It may not seem exciting or glamorous, but keeping your business's statutory affairs in order is vital to your ongoing commercial health and success.

When it comes to submitting such vital financial and non-financial information to official bodies, one small error can result in serious repercussions. As such, working with statutory types of report formats is a water-tight way of keeping track of your affairs and records while significantly reducing the risk of human error.

Armed with interactive insights and dynamic visuals, you will keep your records clean and compliant while gaining the ability to nip any potential errors or issues in the bud.

What Does A Report Look Like?

Now that we’ve covered the most relevant types of reports, we will answer the question: what does a report look like? 

As mentioned at the beginning of this insightful guide, static reporting is a thing of the past. With the rise of modern technologies like self-service BI tools , the use of interactive reports in the shape of business dashboards has become more and more popular among companies.

Unlike static reports that take time to be generated and are difficult to understand, modern reporting tools are intuitive. Their visual nature makes them easy to understand for any type of user, and they provide businesses with a central view of their most important performance indicators for an improved decision-making process. Here, we will cover 20 useful dashboard examples from different industries, functions, and platforms to put the value of dashboard reporting into perspective. 

1. Financial Report

Keeping finances in check is critical for success. This financial report offers an overview of the most important financial metrics that a business needs to monitor its economic activities and answer vital questions to ensure healthy finances. 

With insights about liquidity, invoicing, budgeting, and general financial stability, managers can extract long and short-term conclusions to reduce inefficiencies, make accurate forecasts about future performance, and keep the overall financial efficiency of the business flowing. For instance, getting a detailed calculation of the business's working capital can allow you to understand how liquid your company is. If it's higher than expected, it means you have the potential to invest and grow—definitely, one of the most valuable types of finance reports.

2. Marketing Report 

Our following example is a marketing report that ensures a healthy return on investment from your marketing efforts. This type of report offers a detailed overview of campaign performance over the last 12 weeks. Having access to this information enables you to maximize the value of your promotional actions, keeping your audience engaged by providing a targeted experience. 

For instance, you can implement different campaign formats as a test and then compare which one is most successful for your business. This is possible thanks to the monitoring of important marketing metrics such as the click-through rate (CTR), cost per click (CPC), cost per acquisition (CPA), and more. 

The visual nature of this report makes it easy to understand important insights at a glance. For example, the four gauge charts at the top show the total spending from all campaigns and how much of the total budget of each campaign has been used. In just seconds, you can see if you are on target to meet your marketing budgets for every single campaign. 

3. Sales Report

An intuitive sales dashboard like the one above is the perfect analytical tool to monitor and optimize sales performance. Armed with powerful high-level metrics, this report type is especially interesting for managers, executives, and sales VPs as it provides relevant information to ensure strategic and operational success. 

The value of this sales report lies in the fact that it offers a complete and comprehensive overview of relevant insights needed to make smart sales decisions. For instance, at the top of an analysis tool, you get important metrics such as the number of sales, revenue, profit, and costs, all compared to a set target and to the previous time period. The use of historical data is fundamental when building successful sales strategies as they provide a picture of what could happen in the future. Being able to filter the key metrics all in one screen is a key benefit of modern reporting. 

4. HR Report 

Our next example of a report is about human resources analytics . The HR department needs to track various KPIs for employee performance and effectiveness. But overall, they have to ensure that employees are happy and working in a healthy environment since an unhappy workforce can significantly damage an organization. This is all possible with the help of this intuitive dashboard. 

Providing a comprehensive mix of metrics, this employee-centric report drills down into every major element needed to ensure successful workforce management. For example, the top portion of the dashboard covers absenteeism in 3 different ways: yearly average, absenteeism rate with a target of 3.8%, and absenteeism over the last five years. Tracking absenteeism rates in detail is helpful as it can tell you if your employees are skipping work days. If the rate is over the expected target, then you have to dig deeper into the reasons and find sustainable solutions. 

On the other hand, the second part of the dashboard covers the overall labor effectiveness (OLE). This can be tracked based on specific criteria that HR predefined, and it helps them understand if workers are achieving their targets or if they need extra training or help. 

5. Management Report

Managers must monitor big amounts of information to ensure that the business is running smoothly. One of them being investor relationships. This management dashboard focuses on high-level metrics that shareholders need to look at before investing, such as the return on assets, return on equity, debt-equity ratio, and share price, among others. 

By getting an overview of these important metrics, investors can easily extract the needed information to make an informed decision regarding an investment in your business. For instance, the return on assets measures how efficiently are the company's assets being used to generate profit. With this information, investors can understand how effectively your company deploys available resources compared to others in the market. Another great indicator is the share price; the higher the increase in your share price, the more money your shareholders are making from their investment. 

6. IT Report 

Just like all the other departments and sections covered in this list, the IT department is one that can especially benefit from these types of reports. With so many technical issues to solve, the need for a visual tool to help IT specialists stay on track with their workload becomes critical. 

As seen in the image above, this IT dashboard offers detailed information about different system indicators. For starters, we get a visual overview of the status of each server, followed by a detailed graph displaying the uptime & downtime of each week. This is complemented by the most common downtown issues and some ticket management information. Getting this level of insight helps your IT staff to know what is happening and when it is happening and find proper solutions to prevent these issues from repeating themselves. Keeping constant track of these metrics will ensure robust system performance. 

7. Procurement Report

The following example of a report was built with intuitive procurement analytics software , and it gives a general view of various metrics that the procurement department needs to work with regularly. 

With the possibility to filter, drill down, and interact with KPIs, this intuitive procurement dashboard offers key information to ensure a healthy supplier relationship. With metrics such as compliance rate, the number of suppliers, or the purchase order cycle time, the procurement team can classify the different suppliers, define the relationship each of them has with the company, and optimize processes to ensure it stays profitable.

8. Customer Service Report

Following our list of examples of reports is one from the support area. Armed with powerful customer service KPIs , this dashboard is a useful tool to monitor performance, spot trends, identify strengths and weaknesses, and improve the overall effectiveness of the customer support department. 

Covering aspects such as revenue and costs from customer support as well as customer satisfaction, this complete analysis tool is the perfect tool for managers who have to keep an eye on every little detail from a performance and operational perspective. For example, by monitoring your customer service costs and comparing them to the revenue, you can understand if you are investing the right amount into your support processes. This can be directly related to your agent’s average time to solve issues; the longer it takes to solve a support ticket, the more money it will cost and the less revenue it will bring. If you see that your agents are taking too long to solve an issue, you can think of some training instances to help them reduce this number. 

9. Market Research Report 

This list of report types examples would not be complete without a market research report . Market research agencies deal with a large amount of information coming from surveys and other research sources. Taking all this into account, the need for reports that can be filtered for deeper interaction becomes more necessary for this industry than any other. 

The image above is a brand analytics dashboard that displays the survey results about how the public perceives a brand. This savvy tool contains different charts that make it easy to understand the information visually. For instance, the map chart with the different colors lets you quickly understand in which regions each age range is located. The charts can be filtered further to see the detailed answers from each group for a deeper analysis. 

10. Social Media Report 

Last but not least, we have a social media report .  This scorecard format dashboard monitors the performance of 4 main social media channels: Facebook, Twitter, Instagram, and YouTube, and it serves as a perfect visual overview to track the performance of different social media efforts and achievements. 

Tracking relevant metrics such as followers, impressions, clicks, engagement rates, and conversions, this report type serves as a perfect progress report to show to managers or clients who need to see the status of their social channels. Each metric is shown in its actual value and compared to a set target. The colors green and red from the fourth column let you quickly understand if a metric is over or under its expected target. 

11. Logistics Report

Logistics are the cornerstone of an operationally fluent and progressive business. If you deal with large quantities of goods and tangible items, in particular, maintaining a solid logistical strategy is vital to ensuring you maintain your brand reputation while keeping things flowing in the right direction.

A prime example of the types of data reporting tool designed to improve logistical management, our warehouse KPI dashboard is equipped with metrics required to maintain strategic movement while eliminating any unnecessary costs or redundant processes. Here, you can dig into your shipping success rates across regions while accessing warehouse costs and perfect order rates in real-time. If you spot any potential inefficiencies, you can track them here and take the correct course of action to refine your strategy. This is an essential tool for any business with a busy or scaling warehouse.

12. Manufacturing Report

Next, in our essential types of business reports examples, we’re looking at tools made to improve your business’s various manufacturing processes.

Our clean and concise production tool is a sight to behold and serves up key manufacturing KPIs that improve the decision-making process regarding costs, volume, and machinery.

Here, you can hone in on historical patterns and trends while connecting with priceless real-time insights that will not only help you make the right calls concerning your manufacturing process at the moment but will also help you formulate predictive strategies that will ultimately save money, boost productivity, and result in top-quality products across the board.

13. Retail Report

As a retailer with so many channels to consider and so many important choices to make, working with the right metrics and visuals is absolutely essential. Fortunately, we live in an age where there are different types of reporting designed for this very reason.

Our sales and order example, generated with retail analytics software , is a dream come true for retailers as it offers the visual insights needed to understand your product range in greater detail while keeping a firm grip on your order volumes, perfect order rates, and reasons for returns.

Gaining access to these invaluable insights in one visually presentable space will allow you to track increases or decreases in orders over a set timeframe (and understand whether you’re doing the right things to drive engagement) while plowing your promotional resources into the products that are likely to offer the best returns.

Plus, by gaining an accurate overview of why people are returning your products, you can omit problem items or processes from your retail strategy, improving your brand reputation as well as revenue in the process.

14. Digital Media Report

The content and communications you publish are critical to your ongoing success, regardless of your sector, niche, or specialty. Without putting out communications that speak directly to the right segments of your audience at the right times in their journey, your brand will swiftly fade into the background.

To ensure your brand remains inspiring, engaging, and thought-leading across channels, working with media types of a business report is essential. You must ensure your communications cut through the noise and scream ‘quality’ from start to finish—no ifs, no buts, no exceptions.

Our content quality control tool is designed with a logical hierarchy that will tell you if your content sparks readership, if the language you’re using is inclusive and conversational, and how much engagement-specific communications earn. You can also check your most engaged articles with a quick glance to understand what your users value most. Armed with this information, you can keep creating content that your audience loves and ultimately drives true value to the business.

15. Energy Report

In the age of sustainability and in the face of international fuel hikes, managing the energy your business uses effectively is paramount. Here, there is little room for excess or error, and as such, working with the right metrics is the only way to ensure successful energy regulation.

If your company has a big HQ or multiple sites that require power, our energy management analytics tool will help you take the stress out of managing your resources. One of the most striking features of this dashboard is the fact that it empowers you to compare your company’s energy usage against those from other sectors and set an accurate benchmark.

Here, you can also get a digestible breakdown of your various production costs regarding energy consumption and the main sources you use to keep your organization running. Regularly consulting these metrics will not only help you save colossal chunks of your budget, but it will also give you the intelligence to become more sustainable as an organization. This, in turn, is good for the planet and your brand reputation—a real win-win-win.

16. FMCG Report

The fast-moving consuming goods (FMCG) industry can highly benefit from a powerful report containing real-time insights. This is because the products handled in this sector which are often food and beverages, don’t last very long. Therefore, having a live overview of all the latest developments can help decision-makers optimize the supply chain to ensure everything runs smoothly and no major issues happen. 

Our report format example above aims to do just that by providing an overview of critical performance indicators, such as the percentage of products sold within freshness date, the out-of-stock rate, on-time in full deliveries, inventory turnover, and more.  What makes this template so valuable is the fact that it provides a range of periods to get a more recent view of events but also a longer yearly view to extract deeper insights. 

The FMCG dashboard also offers an overview of the main KPIs to help users understand if they are on the right track to meet their goals. There, we can observe that the OTIF is far from its target of 90%. Therefore, it should be looked at in more detail to optimize it and prevent it from affecting the entire supply chain. 

17. Google Analytics Report

Regardless of the industry you are in, if you have a website then you probably require a  Google Analytics report. This powerful tool helps you understand how your audience interacts with your website while helping you reach more people through the Google search engine. The issue is that the reports the tool provides are more or less basic and don’t give you the dynamic and agile view you need to stay on top of your data and competitors. 

For that reason, at datapine, we generated a range of Google Analytics dashboards that take your experience one step further by allowing you to explore your most important KPIs in real-time. That way, you’ll be able to spot any potential issues or opportunities to improve as soon as they occur, allowing you to act on them on the spot. 

Among some of the most valuable metrics you can find in this sample are the sessions and their daily, weekly, and monthly development, the average session duration, the bounce rate by channel and by top 5 countries, among others.

18. YouTube Report

So far, we’ve covered examples for various industries and sectors. Now, we will dive a bit deeper into some templates related to popular platforms businesses use in their daily operations. With the rise in video-related content, we could not leave YouTube outside of the list. This popular platform hides some valuable insights that can help you improve your content for your current audience but also reach new audiences that can be interested in your products or services. 

This highly visual and dynamic sample offers an interactive view of relevant KPIs to help you understand every aspect of your video performance. The template can be filtered for different videos to help you understand how each type of content performs. For instance, you get an overview of engagement metrics, such as likes, dislikes, comments, and shares, that way, you can understand how your audience interacts with your content.

Additionally, you also get more detailed charts about the number of views, the average watch time per day, and audience retention. These indicators can help you understand if something needs to be changed. For instance, audience retention goes down a lot after one minute and a half. Therefore you either need to make sure you are making the rest of the video a bit more interesting or offering your product or service or any other relevant information in the first minute.

19. LinkedIn Report

Another very important platform that companies use, no matter their size or industry, is LinkedIn. This platform is the place where companies develop and showcase their corporate image, network with other companies, and tell their clients and audience about the different initiatives they are developing to grow and be better. Some organizations also use LinkedIn to showcase their charity or sustainability initiatives. 

The truth is LinkedIn has become an increasingly relevant platform, and just like we discussed with YouTube, organizations need to analyze data to ensure their strategies are on the right path to success. 

The template above offers a 360-degree view of a company page's performance. With metrics such as the followers gained, engagement rate, impressions vs unique impressions, CTR, and more. Decision-makers can dive deeper into the performance of their content and understand what their audience enjoys the most. For instance, by looking at the CTR of the last 5 company updates, you can start to get a sense of what topics and content format your audience on the platforms interact with the most. That way, you’ll avoid wasting time and resources producing content without interaction.

20. Healthcare Report

Moving on from platform-related examples, we have one last monthly report template from a very relevant sector, the healthcare industry. For decades now, hospitals and healthcare professionals have benefited from data to develop new treatments and analyze unknown diseases. But, data can also help to ensure daily patient care is of top quality. 

Our sample above is a healthcare dashboard report that tracks patient satisfaction stats for a clinic named Saint Martins Clinic. The template provides insights into various aspects of patient care that can affect their satisfaction levels to help spot any weak areas. 

Just by looking at the report in a bit more detail, we can already see that the average waiting time for arrival to a bed and time to see a doctor are on the higher side. This is something that needs to be looked into immediately, as waiting times are the most important success factors for patients. Additionally, we can see those lab test turnarounds are also above target. This is another aspect that should be optimized to prevent satisfaction levels from going down.

If you feel inspired by this list and want to see some of the best uses for business reports, then we recommend you take a look at our dashboard examples library, where you will find over 80+ templates from different industries, functions, and platforms for extra inspiration! 

What You Should Look For In A Reporting Tool

As you learned from our extensive list of examples, different types of reports are widely used across industries and sectors. Now, you might wonder, how do I get my hands on one of these reports? The answer is a professional online reporting tool. With the right software in hand, you can generate stunning reports to extract the maximum potential out of your data and boost business growth in the process. 

But, with so many options in the market, how do make sure you choose the best tool for your needs? Below we cover some of the most relevant features and capabilities you should look for to make the most out of the process. 

• Pre-made reporting templates

To ensure successful operations, a business will most likely need to use many types of reports for its internal and external strategies. Manually generating these reports can become a time-consuming task that burdens the business. That is why professional reporting software should offer pre-made reporting templates. At datapine, we offer an extensive template library that allows users to generate reports in a matter of seconds—allowing them to use their time on actually analyzing the information and extracting powerful insights from it. 

• Multiple visualization options

If you look for report templates on Google you might run into multiple posts about written ones. This is not a surprise, as written reports have been the norm for decades. That being said, a modern approach to reporting has developed in the past years where visuals have taken over text. The value of visuals lies in the fact that they make the information easier to understand, especially for users who have no technical knowledge. But most importantly, they make the information easier to explore by telling a compelling story. For that reason, the tool you choose to invest in should provide you with multiple visualization options to have the flexibility to tell your data story in the most successful way possible. 

• Customization 

While pre-made templates are fundamental to generating agile reports, being able to customize them to meet your needs is also of utmost importance. At datapine, we offer our users the possibility to customize their reports to fit their most important KPIs, as well as their logo, business colors, and font. This is an especially valuable feature for external reports that must be shown to clients or other relevant stakeholders, giving your reports a more professional look. Customization can also help from an internal perspective to provide employees who are uncomfortable with data with a familiar environment to work in. 

• Real-time insights 

In the fast-paced world we live in today, having static reports is not enough. Businesses need to have real-time access to the latest developments in their data to spot any issues or opportunities as soon as they occur and act on them to ensure their resources are spent smartly and their strategies are running as expected. Doing so will allow for agile and efficient decision-making, giving the company a huge competitive advantage. 

• Sharing capabilities 

Communication and collaboration are the basis of a successful reporting process. Today, team members and departments need to be connected to ensure everyone is on the right path to achieve general company goals. That is why the tool you invest in should offer flexible sharing capabilities to ensure every user can access the reports. For instance, at datapine, we offer our users the possibility to share reports through automated emails or password-protected URLs with viewing or editing rights depending on what data the specific user can see and manipulate. A great way to keep everyone connected and boost collaboration. 

Types Of Reporting For Every Business & Purpose 

As we’ve seen throughout our journey, different report formats are used by businesses for diverse purposes in their everyday activities. Whether you’re talking about types of reports in research, types of reports in management, or anything in between, these dynamic tools will get you where you need to be (and beyond).

In this post, we covered the top 14 most common ones and explored key examples of how different report types are changing the way businesses are leveraging their most critical insights for internal efficiency and, ultimately, external success.

With modern tools and solutions, reporting doesn’t have to be a tedious task. Anyone in your organization can rely on data for their decision-making process without needing technical skills. Rather, you want to keep your team connected or show progress to investors or clients. There is a report type for the job. To keep your mind fresh, here are the top 14 types of data reports covered in this post: 

• Informational reports 
• Analytical reports 
• Operational reports  
• Product reports 
• Industry reports 
• Department reports 
• Progress reports 
• Internal reports 
• External reports 
• Vertical and lateral reports 
• Strategic reports
• Research reports
• Project reports
• Statutory reports

Now, over to you. Are you ready? If you want to start building your own types of reports and get ahead of the pack today, then you should try our BI reporting software for 14 days for free ! 

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

11.2 Writing a Research Report in American Psychological Association (APA) Style

Learning objectives.

• Identify the major sections of an APA-style research report and the basic contents of each section.
• Plan and write an effective APA-style research report.

In this section, we look at how to write an APA-style empirical research report , an article that presents the results of one or more new studies. Recall that the standard sections of an empirical research report provide a kind of outline. Here we consider each of these sections in detail, including what information it contains, how that information is formatted and organized, and tips for writing each section. At the end of this section is a sample APA-style research report that illustrates many of these principles.

Sections of a Research Report

Title page and abstract.

An APA-style research report begins with a title page . The title is centered in the upper half of the page, with each important word capitalized. The title should clearly and concisely (in about 12 words or fewer) communicate the primary variables and research questions. This sometimes requires a main title followed by a subtitle that elaborates on the main title, in which case the main title and subtitle are separated by a colon. Here are some titles from recent issues of professional journals published by the American Psychological Association.

• Sex Differences in Coping Styles and Implications for Depressed Mood
• Effects of Aging and Divided Attention on Memory for Items and Their Contexts
• Computer-Assisted Cognitive Behavioral Therapy for Child Anxiety: Results of a Randomized Clinical Trial
• Virtual Driving and Risk Taking: Do Racing Games Increase Risk-Taking Cognitions, Affect, and Behavior?

Below the title are the authors’ names and, on the next line, their institutional affiliation—the university or other institution where the authors worked when they conducted the research. As we have already seen, the authors are listed in an order that reflects their contribution to the research. When multiple authors have made equal contributions to the research, they often list their names alphabetically or in a randomly determined order.

It’s Soooo Cute!

How Informal Should an Article Title Be?

In some areas of psychology, the titles of many empirical research reports are informal in a way that is perhaps best described as “cute.” They usually take the form of a play on words or a well-known expression that relates to the topic under study. Here are some examples from recent issues of the Journal of Personality and Social Psychology .

• “Let’s Get Serious: Communicating Commitment in Romantic Relationships”
• “Through the Looking Glass Clearly: Accuracy and Assumed Similarity in Well-Adjusted Individuals’ First Impressions”
• “Don’t Hide Your Happiness! Positive Emotion Dissociation, Social Connectedness, and Psychological Functioning”
• “Forbidden Fruit: Inattention to Attractive Alternatives Provokes Implicit Relationship Reactance”

Individual researchers differ quite a bit in their preference for such titles. Some use them regularly, while others never use them. What might be some of the pros and cons of using cute article titles?

For articles that are being submitted for publication, the title page also includes an author note that lists the authors’ full institutional affiliations, any acknowledgments the authors wish to make to agencies that funded the research or to colleagues who commented on it, and contact information for the authors. For student papers that are not being submitted for publication—including theses—author notes are generally not necessary.

The abstract is a summary of the study. It is the second page of the manuscript and is headed with the word Abstract . The first line is not indented. The abstract presents the research question, a summary of the method, the basic results, and the most important conclusions. Because the abstract is usually limited to about 200 words, it can be a challenge to write a good one.

Introduction

The introduction begins on the third page of the manuscript. The heading at the top of this page is the full title of the manuscript, with each important word capitalized as on the title page. The introduction includes three distinct subsections, although these are typically not identified by separate headings. The opening introduces the research question and explains why it is interesting, the literature review discusses relevant previous research, and the closing restates the research question and comments on the method used to answer it.

The Opening

The opening , which is usually a paragraph or two in length, introduces the research question and explains why it is interesting. To capture the reader’s attention, researcher Daryl Bem recommends starting with general observations about the topic under study, expressed in ordinary language (not technical jargon)—observations that are about people and their behavior (not about researchers or their research; Bem, 2003). Concrete examples are often very useful here. According to Bem, this would be a poor way to begin a research report:

Festinger’s theory of cognitive dissonance received a great deal of attention during the latter part of the 20th century (p. 191)

The following would be much better:

The individual who holds two beliefs that are inconsistent with one another may feel uncomfortable. For example, the person who knows that he or she enjoys smoking but believes it to be unhealthy may experience discomfort arising from the inconsistency or disharmony between these two thoughts or cognitions. This feeling of discomfort was called cognitive dissonance by social psychologist Leon Festinger (1957), who suggested that individuals will be motivated to remove this dissonance in whatever way they can (p. 191).

After capturing the reader’s attention, the opening should go on to introduce the research question and explain why it is interesting. Will the answer fill a gap in the literature? Will it provide a test of an important theory? Does it have practical implications? Giving readers a clear sense of what the research is about and why they should care about it will motivate them to continue reading the literature review—and will help them make sense of it.

Breaking the Rules

Researcher Larry Jacoby reported several studies showing that a word that people see or hear repeatedly can seem more familiar even when they do not recall the repetitions—and that this tendency is especially pronounced among older adults. He opened his article with the following humorous anecdote (Jacoby, 1999).

A friend whose mother is suffering symptoms of Alzheimer’s disease (AD) tells the story of taking her mother to visit a nursing home, preliminary to her mother’s moving there. During an orientation meeting at the nursing home, the rules and regulations were explained, one of which regarded the dining room. The dining room was described as similar to a fine restaurant except that tipping was not required. The absence of tipping was a central theme in the orientation lecture, mentioned frequently to emphasize the quality of care along with the advantages of having paid in advance. At the end of the meeting, the friend’s mother was asked whether she had any questions. She replied that she only had one question: “Should I tip?” (p. 3).

Although both humor and personal anecdotes are generally discouraged in APA-style writing, this example is a highly effective way to start because it both engages the reader and provides an excellent real-world example of the topic under study.

The Literature Review

Immediately after the opening comes the literature review , which describes relevant previous research on the topic and can be anywhere from several paragraphs to several pages in length. However, the literature review is not simply a list of past studies. Instead, it constitutes a kind of argument for why the research question is worth addressing. By the end of the literature review, readers should be convinced that the research question makes sense and that the present study is a logical next step in the ongoing research process.

Like any effective argument, the literature review must have some kind of structure. For example, it might begin by describing a phenomenon in a general way along with several studies that demonstrate it, then describing two or more competing theories of the phenomenon, and finally presenting a hypothesis to test one or more of the theories. Or it might describe one phenomenon, then describe another phenomenon that seems inconsistent with the first one, then propose a theory that resolves the inconsistency, and finally present a hypothesis to test that theory. In applied research, it might describe a phenomenon or theory, then describe how that phenomenon or theory applies to some important real-world situation, and finally suggest a way to test whether it does, in fact, apply to that situation.

Looking at the literature review in this way emphasizes a few things. First, it is extremely important to start with an outline of the main points that you want to make, organized in the order that you want to make them. The basic structure of your argument, then, should be apparent from the outline itself. Second, it is important to emphasize the structure of your argument in your writing. One way to do this is to begin the literature review by summarizing your argument even before you begin to make it. “In this article, I will describe two apparently contradictory phenomena, present a new theory that has the potential to resolve the apparent contradiction, and finally present a novel hypothesis to test the theory.” Another way is to open each paragraph with a sentence that summarizes the main point of the paragraph and links it to the preceding points. These opening sentences provide the “transitions” that many beginning researchers have difficulty with. Instead of beginning a paragraph by launching into a description of a previous study, such as “Williams (2004) found that…,” it is better to start by indicating something about why you are describing this particular study. Here are some simple examples:

Another example of this phenomenon comes from the work of Williams (2004).

Williams (2004) offers one explanation of this phenomenon.

An alternative perspective has been provided by Williams (2004).

We used a method based on the one used by Williams (2004).

Finally, remember that your goal is to construct an argument for why your research question is interesting and worth addressing—not necessarily why your favorite answer to it is correct. In other words, your literature review must be balanced. If you want to emphasize the generality of a phenomenon, then of course you should discuss various studies that have demonstrated it. However, if there are other studies that have failed to demonstrate it, you should discuss them too. Or if you are proposing a new theory, then of course you should discuss findings that are consistent with that theory. However, if there are other findings that are inconsistent with it, again, you should discuss them too. It is acceptable to argue that the balance of the research supports the existence of a phenomenon or is consistent with a theory (and that is usually the best that researchers in psychology can hope for), but it is not acceptable to ignore contradictory evidence. Besides, a large part of what makes a research question interesting is uncertainty about its answer.

The Closing

The closing of the introduction—typically the final paragraph or two—usually includes two important elements. The first is a clear statement of the main research question or hypothesis. This statement tends to be more formal and precise than in the opening and is often expressed in terms of operational definitions of the key variables. The second is a brief overview of the method and some comment on its appropriateness. Here, for example, is how Darley and Latané (1968) concluded the introduction to their classic article on the bystander effect:

These considerations lead to the hypothesis that the more bystanders to an emergency, the less likely, or the more slowly, any one bystander will intervene to provide aid. To test this proposition it would be necessary to create a situation in which a realistic “emergency” could plausibly occur. Each subject should also be blocked from communicating with others to prevent his getting information about their behavior during the emergency. Finally, the experimental situation should allow for the assessment of the speed and frequency of the subjects’ reaction to the emergency. The experiment reported below attempted to fulfill these conditions (p. 378).

Thus the introduction leads smoothly into the next major section of the article—the method section.

The method section is where you describe how you conducted your study. An important principle for writing a method section is that it should be clear and detailed enough that other researchers could replicate the study by following your “recipe.” This means that it must describe all the important elements of the study—basic demographic characteristics of the participants, how they were recruited, whether they were randomly assigned, how the variables were manipulated or measured, how counterbalancing was accomplished, and so on. At the same time, it should avoid irrelevant details such as the fact that the study was conducted in Classroom 37B of the Industrial Technology Building or that the questionnaire was double-sided and completed using pencils.

The method section begins immediately after the introduction ends with the heading “Method” (not “Methods”) centered on the page. Immediately after this is the subheading “Participants,” left justified and in italics. The participants subsection indicates how many participants there were, the number of women and men, some indication of their age, other demographics that may be relevant to the study, and how they were recruited, including any incentives given for participation.

Figure 11.1 Three Ways of Organizing an APA-Style Method

After the participants section, the structure can vary a bit. Figure 11.1 “Three Ways of Organizing an APA-Style Method” shows three common approaches. In the first, the participants section is followed by a design and procedure subsection, which describes the rest of the method. This works well for methods that are relatively simple and can be described adequately in a few paragraphs. In the second approach, the participants section is followed by separate design and procedure subsections. This works well when both the design and the procedure are relatively complicated and each requires multiple paragraphs.

What is the difference between design and procedure? The design of a study is its overall structure. What were the independent and dependent variables? Was the independent variable manipulated, and if so, was it manipulated between or within subjects? How were the variables operationally defined? The procedure is how the study was carried out. It often works well to describe the procedure in terms of what the participants did rather than what the researchers did. For example, the participants gave their informed consent, read a set of instructions, completed a block of four practice trials, completed a block of 20 test trials, completed two questionnaires, and were debriefed and excused.

In the third basic way to organize a method section, the participants subsection is followed by a materials subsection before the design and procedure subsections. This works well when there are complicated materials to describe. This might mean multiple questionnaires, written vignettes that participants read and respond to, perceptual stimuli, and so on. The heading of this subsection can be modified to reflect its content. Instead of “Materials,” it can be “Questionnaires,” “Stimuli,” and so on.

The results section is where you present the main results of the study, including the results of the statistical analyses. Although it does not include the raw data—individual participants’ responses or scores—researchers should save their raw data and make them available to other researchers who request them. Some journals now make the raw data available online.

Although there are no standard subsections, it is still important for the results section to be logically organized. Typically it begins with certain preliminary issues. One is whether any participants or responses were excluded from the analyses and why. The rationale for excluding data should be described clearly so that other researchers can decide whether it is appropriate. A second preliminary issue is how multiple responses were combined to produce the primary variables in the analyses. For example, if participants rated the attractiveness of 20 stimulus people, you might have to explain that you began by computing the mean attractiveness rating for each participant. Or if they recalled as many items as they could from study list of 20 words, did you count the number correctly recalled, compute the percentage correctly recalled, or perhaps compute the number correct minus the number incorrect? A third preliminary issue is the reliability of the measures. This is where you would present test-retest correlations, Cronbach’s α, or other statistics to show that the measures are consistent across time and across items. A final preliminary issue is whether the manipulation was successful. This is where you would report the results of any manipulation checks.

The results section should then tackle the primary research questions, one at a time. Again, there should be a clear organization. One approach would be to answer the most general questions and then proceed to answer more specific ones. Another would be to answer the main question first and then to answer secondary ones. Regardless, Bem (2003) suggests the following basic structure for discussing each new result:

• Remind the reader of the research question.
• Give the answer to the research question in words.
• Present the relevant statistics.
• Qualify the answer if necessary.
• Summarize the result.

Notice that only Step 3 necessarily involves numbers. The rest of the steps involve presenting the research question and the answer to it in words. In fact, the basic results should be clear even to a reader who skips over the numbers.

The discussion is the last major section of the research report. Discussions usually consist of some combination of the following elements:

• Summary of the research
• Theoretical implications
• Practical implications
• Limitations
• Suggestions for future research

The discussion typically begins with a summary of the study that provides a clear answer to the research question. In a short report with a single study, this might require no more than a sentence. In a longer report with multiple studies, it might require a paragraph or even two. The summary is often followed by a discussion of the theoretical implications of the research. Do the results provide support for any existing theories? If not, how can they be explained? Although you do not have to provide a definitive explanation or detailed theory for your results, you at least need to outline one or more possible explanations. In applied research—and often in basic research—there is also some discussion of the practical implications of the research. How can the results be used, and by whom, to accomplish some real-world goal?

The theoretical and practical implications are often followed by a discussion of the study’s limitations. Perhaps there are problems with its internal or external validity. Perhaps the manipulation was not very effective or the measures not very reliable. Perhaps there is some evidence that participants did not fully understand their task or that they were suspicious of the intent of the researchers. Now is the time to discuss these issues and how they might have affected the results. But do not overdo it. All studies have limitations, and most readers will understand that a different sample or different measures might have produced different results. Unless there is good reason to think they would have, however, there is no reason to mention these routine issues. Instead, pick two or three limitations that seem like they could have influenced the results, explain how they could have influenced the results, and suggest ways to deal with them.

Most discussions end with some suggestions for future research. If the study did not satisfactorily answer the original research question, what will it take to do so? What new research questions has the study raised? This part of the discussion, however, is not just a list of new questions. It is a discussion of two or three of the most important unresolved issues. This means identifying and clarifying each question, suggesting some alternative answers, and even suggesting ways they could be studied.

Finally, some researchers are quite good at ending their articles with a sweeping or thought-provoking conclusion. Darley and Latané (1968), for example, ended their article on the bystander effect by discussing the idea that whether people help others may depend more on the situation than on their personalities. Their final sentence is, “If people understand the situational forces that can make them hesitate to intervene, they may better overcome them” (p. 383). However, this kind of ending can be difficult to pull off. It can sound overreaching or just banal and end up detracting from the overall impact of the article. It is often better simply to end when you have made your final point (although you should avoid ending on a limitation).

The references section begins on a new page with the heading “References” centered at the top of the page. All references cited in the text are then listed in the format presented earlier. They are listed alphabetically by the last name of the first author. If two sources have the same first author, they are listed alphabetically by the last name of the second author. If all the authors are the same, then they are listed chronologically by the year of publication. Everything in the reference list is double-spaced both within and between references.

Appendixes, Tables, and Figures

Appendixes, tables, and figures come after the references. An appendix is appropriate for supplemental material that would interrupt the flow of the research report if it were presented within any of the major sections. An appendix could be used to present lists of stimulus words, questionnaire items, detailed descriptions of special equipment or unusual statistical analyses, or references to the studies that are included in a meta-analysis. Each appendix begins on a new page. If there is only one, the heading is “Appendix,” centered at the top of the page. If there is more than one, the headings are “Appendix A,” “Appendix B,” and so on, and they appear in the order they were first mentioned in the text of the report.

After any appendixes come tables and then figures. Tables and figures are both used to present results. Figures can also be used to illustrate theories (e.g., in the form of a flowchart), display stimuli, outline procedures, and present many other kinds of information. Each table and figure appears on its own page. Tables are numbered in the order that they are first mentioned in the text (“Table 1,” “Table 2,” and so on). Figures are numbered the same way (“Figure 1,” “Figure 2,” and so on). A brief explanatory title, with the important words capitalized, appears above each table. Each figure is given a brief explanatory caption, where (aside from proper nouns or names) only the first word of each sentence is capitalized. More details on preparing APA-style tables and figures are presented later in the book.

Sample APA-Style Research Report

Figure 11.2 “Title Page and Abstract” , Figure 11.3 “Introduction and Method” , Figure 11.4 “Results and Discussion” , and Figure 11.5 “References and Figure” show some sample pages from an APA-style empirical research report originally written by undergraduate student Tomoe Suyama at California State University, Fresno. The main purpose of these figures is to illustrate the basic organization and formatting of an APA-style empirical research report, although many high-level and low-level style conventions can be seen here too.

Figure 11.2 Title Page and Abstract

This student paper does not include the author note on the title page. The abstract appears on its own page.

Figure 11.3 Introduction and Method

Note that the introduction is headed with the full title, and the method section begins immediately after the introduction ends.

Figure 11.4 Results and Discussion

The discussion begins immediately after the results section ends.

Figure 11.5 References and Figure

If there were appendixes or tables, they would come before the figure.

Key Takeaways

• An APA-style empirical research report consists of several standard sections. The main ones are the abstract, introduction, method, results, discussion, and references.
• The introduction consists of an opening that presents the research question, a literature review that describes previous research on the topic, and a closing that restates the research question and comments on the method. The literature review constitutes an argument for why the current study is worth doing.
• The method section describes the method in enough detail that another researcher could replicate the study. At a minimum, it consists of a participants subsection and a design and procedure subsection.
• The results section describes the results in an organized fashion. Each primary result is presented in terms of statistical results but also explained in words.
• The discussion typically summarizes the study, discusses theoretical and practical implications and limitations of the study, and offers suggestions for further research.
• Practice: Look through an issue of a general interest professional journal (e.g., Psychological Science ). Read the opening of the first five articles and rate the effectiveness of each one from 1 ( very ineffective ) to 5 ( very effective ). Write a sentence or two explaining each rating.
• Practice: Find a recent article in a professional journal and identify where the opening, literature review, and closing of the introduction begin and end.
• Practice: Find a recent article in a professional journal and highlight in a different color each of the following elements in the discussion: summary, theoretical implications, practical implications, limitations, and suggestions for future research.

Bem, D. J. (2003). Writing the empirical journal article. In J. M. Darley, M. P. Zanna, & H. R. Roediger III (Eds.), The compleat academic: A practical guide for the beginning social scientist (2nd ed.). Washington, DC: American Psychological Association.

Darley, J. M., & Latané, B. (1968). Bystander intervention in emergencies: Diffusion of responsibility. Journal of Personality and Social Psychology, 4 , 377–383.

Research Methods in Psychology Copyright © 2016 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Report Writing Guide

Report generator.

How is writing a report any different from writing an essay ?

• Article Writing Examples & Samples
• Memo Writing Examples & Samples

Unlike an ordinary essay, reports are lengthy and concise in form. They follow a formal structure and are used to convey the results or findings of a given study. Knowing how to write a report is essential in communication. You want to make sure that its target readers clearly understand the message being delivered. These types of documents are usually assessed based on its content, structure, format or layout, language, and referencing. Because of this, a writer must focus on the main purpose of the report, and how they may communicate in such a way that will cater its audience. You may also see writing templates & examples .

Although there are many ways to write a report, here are some basic steps to guide you through:

1. Determine What the Report Is about.

Understanding the subject of your report is the first and the most important step of the process. You need to determine what the assignment is asking from you, and what purpose does it serve. You may also see free writing examples .

In order to discover what the report is about, begin by reading the instructions or information given regarding the report, and proceed by asking yourself the following questions:

• What should the report be about?  Identify what the main topic of the report is, and what must be tackled in its content. You may also like book writing examples & samples .
• What is needed?  Determine what resources are needed, such as surveys or questionnaires, to complete the report.
• When is it due?  Since most reports are academic-related, they often have a specific due date that will help you come up with a timeline for the research process. You may also check out script writing examples & samples .
• Who is its target audience or proponents?  When it comes to report writing, you need to keep your audience in mind. This may consist of the general public, a customer or client, or of any specific demographic.

Once you have found the answers to these points, you can then identify the scope and limitations of the assignment.

2. Do Your Research.

The next step is to find the information needed to create the report. However, this would greatly depend on the type of report being written as well. You might be interested in tips for writing an effective essay .

For instance, a journalistic report would require facts about a given topic. This may involve gaining personal testimonies from significant individuals, observing certain people, activities, or events, or reading a published material. Ensure that the information gathered is relevant, appropriate, and reliable. What you have collected from this step will serve as a basis for the body of the report, along with its findings.

3. Decide on a Structure.

Reports generally follow a similar structure. A case study report , a status report , and an incident report all share a common purpose, yet they may slightly differ in terms of their length and tone.

Depending on the type of report being created, the standard structure of a report consists of the following parts:

• Summary or Abstract
• Table of contents
• Introduction
• Terms of reference (Scope & Limitations)
• Conclusions
• Recommendations
• References or Bibliography

Each section of a report may also be composed of headings and subheadings that are used to break down complex ideas into specific details. You may also see what do you mean by writing skills?

4. Create a Draft.

By now, you should be able to draft the content of your report. Keep in mind that report writing involves a thorough process of learning, formal writing , and analyzing concepts and theories from the available references. With the information garnered from your sources, you can then proceed to the findings of your report.

The findings are typically the results drawn from your readings, experiments, observations, and interviews. Your research activity, which is found in the procedures or methodology section of the document, must be indicated to prove your findings are reliable. It’s also necessary to provide accurate descriptions of how the process was conducted and what materials were used. Depending on the type of report written, the findings may include photos, graphs, tables, or any visual representation that can help support your claims. You may also like essay writing examples & samples .

Any additional details that may complement information stated in the report — like spreadsheets, forms, and brochures — may be included in the appendices.

5. Analyze Your Findings and Form Conclusions.

This is the part where you need to examine what you have gathered, and interpret what you have found to draw conclusions. This may explain why a certain situation occurred, what this means for an entity, and what is likely to happen if this event continues (or discontinues). Remember, the conclusion shouldn’t serve as a mere summary rather, a collection of facts that explain the significant details of your findings and what it suggests. You wouldn’t need to provide an explanation for your results unless a discussion is asked from you. You may also see informative writing examples & samples .

6. Provide Recommendations.

Recommendations typically imply what the researchers think should happen next. This involves the succeeding actions that its readers, specifically those who asked for the report, should do or not do. For instance, students who write school reports often target the academe and its members. So as part of their recommendation, the authors would direct future researchers to enhance certain areas of the report that have not been thoroughly addressed. It’s important to include enough details for the readers to be guided in terms of what must be done and who should do it.

7. Formulate a Summary and Table of Contents.

For reports that do require an executive summary , remember to do this by the very end of the report writing. This must be kept brief and to-the-point, where a maximum of 100 words would be enough to carry out your message. It should provide readers with a gist of what the report is about, as well as a summary of the recommendations.

Once you have finalized each section of the report, you can then create a list of its contents. This should be arranged according to how the report is structured. You may also indicate the page number of each section to make it easier for readers to find what they’re looking for.

8. Compile Your References.

At the beginning of the report writing process, you may have collected information from a number of print and online sources to support your study. These references must be compiled and arranged by following the standard APA format once you have already completed your findings. Insert this section at the back portion of your report, or as indicated in the instructions given. Take note that this reference list may also serve as a basis for readers to determine the credibility of the said report. You may also see what is writing used for?

Before printing or submitting the report, it’s always advisable to proofread and recheck the document for any gaps. Make sure you have accomplished everything that needed to be done by reviewing the instructions and guidelines of the assignment, along with the proposed marking schedule. Terms, symbols, abbreviations, and illustrations used in the report must also be explained. Besides that, ensure that the format, numbering, headings, spelling, and grammar of your report are consistent and correct to avoid any problems. You may also like essay writing examples .

If you have enough time to spare, you may even prepare several drafts to review before finalizing your report. You can also have a friend or adviser check your report for assurance. When finished, remember to study the report, as you may be asked to present it in front of an audience. You may also check out summary writing examples and samples .

Text prompt

• Instructive
• Professional

Generate a report on the impact of technology in the classroom on student learning outcomes

Prepare a report analyzing the trends in student participation in sports and arts programs over the last five years at your school.

Purdue Online Writing Lab Purdue OWL® College of Liberal Arts

Welcome to the Purdue Online Writing Lab

Welcome to the Purdue OWL

This page is brought to you by the OWL at Purdue University. When printing this page, you must include the entire legal notice.

Copyright ©1995-2018 by The Writing Lab & The OWL at Purdue and Purdue University. All rights reserved. This material may not be published, reproduced, broadcast, rewritten, or redistributed without permission. Use of this site constitutes acceptance of our terms and conditions of fair use.

The Online Writing Lab at Purdue University houses writing resources and instructional material, and we provide these as a free service of the Writing Lab at Purdue. Students, members of the community, and users worldwide will find information to assist with many writing projects. Teachers and trainers may use this material for in-class and out-of-class instruction.

The Purdue On-Campus Writing Lab and Purdue Online Writing Lab assist clients in their development as writers—no matter what their skill level—with on-campus consultations, online participation, and community engagement. The Purdue Writing Lab serves the Purdue, West Lafayette, campus and coordinates with local literacy initiatives. The Purdue OWL offers global support through online reference materials and services.

A Message From the Assistant Director of Content Development 

The Purdue OWL® is committed to supporting  students, instructors, and writers by offering a wide range of resources that are developed and revised with them in mind. To do this, the OWL team is always exploring possibilties for a better design, allowing accessibility and user experience to guide our process. As the OWL undergoes some changes, we welcome your feedback and suggestions by email at any time.

Please don't hesitate to contact us via our contact page  if you have any questions or comments.

All the best,

Social Media

Facebook twitter.

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• My Account Login
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Perspective
• Open access
• Published: 03 June 2024

Scientific integrity and U.S. “Billion Dollar Disasters”

• Roger Pielke Jr 1 , 2  

npj Natural Hazards volume  1 , Article number:  12 ( 2024 ) Cite this article

1434 Accesses

12 Altmetric

Metrics details

• Attribution
• Climate-change impacts
• Climate sciences

For more than two decades, the U.S. National Oceanic and Atmospheric Administration (NOAA) has published a count of weather-related disasters in the United States that it estimates have exceeded one billion dollars (inflation adjusted) in each calendar year starting in 1980. The dataset is widely cited and applied in research, assessment and invoked to justify policy in federal agencies, Congress and by the U.S. President. This paper performs an evaluation of the dataset under criteria of procedure and substance defined under NOAA’s Information Quality and Scientific Integrity policies. The evaluation finds that the “billion dollar disaster” dataset falls short of meeting these criteria. Thus, public claims promoted by NOAA associated with the dataset and its significance are flawed and at times misleading. Specifically, NOAA incorrectly claims that for some types of extreme weather, the dataset demonstrates detection and attribution of changes on climate timescales. Similarly flawed are NOAA’s claims that increasing annual counts of billion dollar disasters are in part a consequence of human caused climate change. NOAA’s claims to have achieved detection and attribution are not supported by any scientific analysis that it has performed. Given the importance and influence of the dataset in science and policy, NOAA should act quickly to address this scientific integrity shortfall.

Similar content being viewed by others

The global historical climate database HCLIM

The evolving landscape of sea-level rise science from 1990 to 2021

No evidence that mandatory open data policies increase error correction

Introduction.

In the late 1990s, the U.S. National Oceanic and Atmospheric Administration (NOAA) began publishing a tally of weather and climate disasters that each resulted in more than $1 billion in damage, noting that the time series had become “one of our more popular web pages” 1 . Originally, the data was reported in current-year U.S. dollars. In 2011, following criticism that the dataset was misleading, NOAA modified its methods to adjusted historical losses to constant-year dollars by accounting for inflation ( https://www.washingtonpost.com/blogs/capital-weather-gang/post/2011-billion-dollar-weather-disaster-record-legit-or-bad-economics/2012/01/12/gIQADocztP_blog.html ).

By 2023, the billion dollar disaster time series had become a fixture in NOAA’s public outreach, was highlighted by the U.S. government’s U.S. Global Change Research Program (USGCRP) as a “climate change indicator” ( https://storymaps.arcgis.com/collections/ad628a4d3e7e4460b089d9fe96b2475d?item=1 ), was a cited as evidence in support of a “key message” of the Fifth U.S. National Climate Assessment showing that “extreme events are becoming more frequent and severe” ( https://nca2023.globalchange.gov/chapter/2/ ). The time series is often cited in policy settings as evidence of the effects of human-caused climate change to increase the frequency and intensity of extreme weather events and associated economic damage, including in federal agencies, Congress and by the U.S. President ( https://www.congress.gov/bill/118th-congress/house-bill/598/text ; https://www.whitehouse.gov/briefing-room/statements-releases/2023/11/14/fact-sheet-biden-harris-administration-releases-fifth-national-climate-assessment-and-announces-more-than-6-billion-to-strengthen-climate-resilience-across-the-country ). In addition to being widely cited in justifications of policy, as of March, 2024, NOAA’s billion dollar dataset has been cited in almost 1000 articles according to Google Scholar ( https://scholar.google.com/scholar?hl=en&as_sdt=0%2C6&q=%22billion+dollar+disasters%22&btnG= ).

This paper evaluates the billion dollar disaster time series by applying criteria of NOAA’s Information Quality and Scientific Integrity policies. The evaluation finds that billion dollar disaster time series fails to meet NOAA’s criteria for “information quality,” specifically, NOAA’s criteria of traceability, transparency, presentation, and substance.

Thus, the billion dollar disaster dataset is not simply an insufficient basis for claims of the detection and attribution of changes in climate variables (or a consequence of such changes), but the dataset is inappropriate for use in such research. Throughout, I use the terms “detection” and “attribution” as defined by the Intergovernmental panel on Climate Change (IPCC) 2 . Climate data should be the basis for claims of detection and attribution of changes in climate variables, not economic loss data. Because of the shortfalls in scientific integrity documented in this evaluation, policy makers and the public have been misinformed about extreme events and disasters in the United States.

Evaluation of policy or program performance is among the most common and influential practices in applied policy research. Policy evaluation tells us if actions by government programs and agencies are meeting their stated goals and provides insight into reasons for successes and failures. As such, evaluation offers important input that empowers policy makers to correct course and supports efforts by the public to hold governments democratically accountable. A systematic evaluation includes four distinct intellectual tasks 3 , 4 : (a) identification of goals to be achieved, (b) metrics which can be used to assess progress (or lack thereof) with respect to goals, (c) data or evidence related to such metrics, and finally, if possible, (d) judgments of responsibility for observed outcomes.

NOAA’s billion dollar disaster time series is considered a “fundamental research communication” under the Public Communications order of NOAA’s parent agency, the Department of Commerce ( https://www.osec.doc.gov/opog/dmp/daos/dao219_1.html ). NOAA defines a “fundamental research communication” to be “official work regarding the products of basic or applied research in science and engineering, the results of which ordinarily are published and shared broadly within the scientific community” ( https://www.noaa.gov/sites/default/files/legacy/document/2021/Feb/202-735-D.pdf ). NOAA further identifies an important subset of “fundamental research communications” to be “influential information,” which “means information the agency reasonably can determine will have or does have a clear and substantial impact on important public policies or private sector decisions” ( https://www.noaa.gov/organization/information-technology/policy-oversight/information-quality/information-quality-guidelines ). The billion dollar disaster dataset is also what the Office of Management and Budget defines as “Influential Scientific Information” ( https://www.govinfo.gov/content/pkg/FR-2005-01-14/pdf/05-769.pdf ).

NOAA’s Information Quality and Scientific Integrity policies set forth the criteria to be used for evaluating “fundamental research communications,” including the subset of “influential information.” Specifically, NOAA’s Information Quality Guidelines identify three criteria of information quality: utility, objectivity, and integrity ( https://www.noaa.gov/organization/information-technology/policy-oversight/information-quality/information-quality-guidelines ).

Utility refers to “the usefulness of research to its intended users, including the public,” with an emphasis on “transparency.” NOAA’s Scientific Integrity Policy provides further guidance: “Transparency, traceability, and integrity at all levels are required” in order for the agency “to achieve” its mission ( https://www.noaa.gov/sites/default/files/legacy/document/2021/Feb/202-735-D.pdf ).

Traceability: “The ability to verify sources, data, information, methodology, results, assessments, research, analysis, conclusions or other evidence to establish the integrity of findings.”

Transparency: “Characterized by visibility or accessibility of information.”

Objectivity refers to presentation and substance:

Presentation: “includes whether disseminated information is presented in an accurate, clear, complete, and unbiased manner and in a proper context.”

Substance: “involves a focus on ensuring accurate, reliable, and unbiased information. In a scientific, financial, or statistical context, the original and supporting data shall be generated, and the analytic results shall be developed, using sound statistical and research methods.”

Integrity refers to “security ‑ the protection of information from unauthorized access or revision, to ensure that the information is not compromised through corruption or falsification.” Integrity will not be further considered as part of this evaluation.

NOAA’s Scientific Integrity Policy also states that it will “ensure that data and research used to support policy decisions undergo independent peer review by qualified experts” ( https://sciencecouncil.noaa.gov/scientific-integrity-commons/sic-integrity-policy/ ). OMB requires that agencies develop “a transparent process for public disclosure of peer review planning, including a Web-accessible description of the peer review plan that the agency has developed for each of its forthcoming influential scientific disseminations” ( https://www.govinfo.gov/content/pkg/FR-2005-01-14/pdf/05-769.pdf ). There is no such plan in place for the NOAA “billion dollar” dataset and the methods, which have evolved over time, and results have not been subject to any public or transparent form of peer review.

The evaluation conducted here thus focuses on traceability and transparency (as elements of utility) and presentation and substance (as elements of objectivity).

Traceability and transparency

The NOAA billion dollar disaster dataset is intransparent in many ways, including its sources, input data and methodologies employed to produce results. The intransparency includes elements of event loss estimation, additions to and subtractions of events from the database, and adjustments made to historical loss estimates. There have been an unknown number of versions of the dataset, which have not been documented or made publicly available. Changes are made to the dataset more frequently than annually, suggesting that there have been many dozens of versions of the dataset over the past decades. Replication of the dataset or changes made to it is thus not possible by any independent researcher, as is verification or evaluation of the dataset itself.

Seven examples illustrate the lack of transparency and lack of traceability.

First, NOAA states that it utilizes more than “a dozen sources” to “help capture the total, direct costs (both insured and uninsured) of the weather and climate events” ( https://www.ncei.noaa.gov/access/billions/faq ). However, NOAA does not specifically identify these sources in relation to specific events, how its estimates are derived from these sources, or the estimates themselves. Almost all data sources that NOAA cites that it relies on for loss estimates are public agencies that produce data released to the public. Insured losses for specific events are aggregated and typically made available to the public, such as by the Florida Office of Insurance Regulation ( https://www.floir.com/home ). Aggregated data provides no information on specific businesses or individuals.

NOAA also states that it includes in it loss estimates various indirect losses such as business interruption, wildfire suppression and others. NOAA does not provide the data or methods for its estimation of such indirect losses. Smith and Matthews 5 (who also have created and maintained the dataset as NOAA employees) also identify livestock feeding costs as a function of national feedstock trends as a variable used in compiling the dataset. Livestock feeding costs are not considered a disaster cost in conventional disaster accounting methods (such as by NOAA Storm Data or SHELDUS), as these are not direct losses due to a local or regional extreme event, but rather an estimate of national market changes in commodity prices which are influenced by many more factors than an extreme event. It is unclear what other measures of indirect costs are included in the NOAA tabulation.

Second, consider the case of Hurricane Idalia, which made landfall in the Big Bend Region of Florida in late September 2023. Initial catastrophe model estimates suggested insured losses of $2.5 to 5 billion ( https://www.insurancejournal.com/news/national/2023/09/05/738970.htm ). The initial NOAA estimate reported on its billion dollar disaster website in the immediate aftermath of the storm was $2.5 billion. However, actual insured losses have been far less than was estimated in the storm’s aftermath, totaling officially about $310 million through mid-November 2023 ( https://www.floir.com/home/idalia ). The historical practice of NOAA’s National Hurricane Center for estimating total direct hurricane damage was to double insured losses to arrive at an estimate of total direct losses 6 . Even accounting for some additional insurance claims to be made, it is unlikely that Idalia would reach $1 billion in total direct losses under the NHC methodology. Yet by December 2023 NOAA had increased its loss estimate for Idalia to $3.6 billion. What is the basis for NOAA’s estimate of Idalia’s total losses being ~12 times insured losses? That is unknown.

Third, similarly unknown is why historical events are periodically added and removed from the dataset. For instance, from a version of the dataset available in December 2022 to an update published in July 2023, 10 new events were added and 3 were deleted (Fig. 1 ). A later comparison with yet another version of the dataset indicates 4 additional historical events were added (not shown in Fig. 1 ). There is no documentation or justification for such changes, I am only aware of them through the happenstance of downloading the currently available dataset at different times.

Undocumented changes to disaster counts made by NOAA between two different versions of the billion dollar disaster dataset, one downloaded in 2022 and another in 2023.

Fourth, a comparison of event loss estimates from the 2022 dataset and the 2023 version shows that each individual event has been adjusted by a different amount. According to NOAA, the only annual adjustment acknowledged is for inflation based on the Consumer Price Index (CPI). From 2022 to 2023, most of the adjustments made to individual events are between 4.5% and 6% but nine events are adjusted from 6.6% to 145%, and one is a reduction of about 75%. An annual adjustment for CPI should be constant across all events. No documentation is provided to explain these various adjustments and why they are unique to each event.

Fifth, NOAA states that they perform “key transformations” of loss data estimates by “scaling up insured loss data to account for uninsured and underinsured losses, which differs by peril, geography, and asset class.” NOAA makes no details available on the methodology or basis for such transformations, nor their impact on loss estimates, nor how these transformations may change over time.

Similarly, Smith and Matthews 5 reference an overall bias correction that has been applied to the dataset, as well as an additional correction for crop insurance losses. Smith and Katz 6 reference other adjustments, such as an adjustment to U.S. flood insurance participation rates, but neither the methodologies nor results of these various adjustments are documented, nor has the baseline data to which the adjustments are applied. Table 3 from Smith and Katz 7 suggests an open-ended formulaic approach to loss estimation, but none of the data that would be used in such formulas is available. Nor is it clear that NOAA currently applies the formula to loss estimation. If so, it should be straightforward to provide sources, data and methods for each iteration of the dataset.

Sixth, the number of smaller disasters ranging from $1 to $2 billion was fairly constant from 1980 to 2007 and then sharply increased starting in 2008 (Fig. 2 ). NOAA states that “we introduce events into the time series as they “inflate” their way above $1B in costs in today’s dollars. Every year, this leads to the introduction of several new events added from earlier in the time series” ( https://sciencecouncil.noaa.gov/scientific-integrity-commons/sic-integrity-policy/ ). However, the December 2023 dataset shows a net change of zero events from $1-2 billion for the period of 1980–2000 and a net increase of such 2 events from 2001–2023. NOAA’s statement that it elevates disasters from <1 billion in losses to the billion dollar disaster database also indicates that NOAA has another dataset with sub-billion dollar events that is not publicly available.

Increasing disaster counts costing $1-2 billion in a version of NOAA’s 2023 dataset.

The sharp discontinuity in the counts of $1-2 billion events starting in 2008 is suggestive of a change in disaster accounting methods, however, the lack of transparency into the creation of the dataset makes it impossible to know the reasons that may underlie this discontinuity.

Seventh, a comparison of 2023 CPI-adjusted official losses of NOAA’s National Hurricane Center (NHC)20 to the loss estimates of the 2023 NOAA billion dollar dataset (BDD), for significant hurricanes shows large differences (Table 1 ).

The NOAA billion dollar disaster estimates are in all cases except Hurricane Andrew substantially higher than the CPI-adjusted estimates based on the official estimates of NHC. There is no obvious pattern to the differences and the lack of methodological and data transparency makes it impossible to understand why there are such large differences and why these differences vary by such a great deal.

These seven examples indicate clearly that the NOAA billion dollar dataset fails with respect to NOAA’s scientific integrity criteria of traceability and transparency. The many issues and questions raised above cannot be answered because it is impossible to verify sources, data or methodology to establish the integrity of findings. These seven examples are just a small subset of issues that I have raised in public forums about the provenance, methods, and publicly communicated results of the application of these methods. The billion dollar dataset thus does not meet NOAA’s requirement that data be transparent and traceable.

Presentation and substance

Even in the absence of the issues documented above, the NOAA billion dollar disaster dataset is potentially misleading, because it has been represented by NOAA and U.S. government officials as evidence of the detection of trends in extreme weather phenomena and the attribution of those trends to human-caused climate change due to the emission of greenhouse gases.

For instance:

The NOAA official responsible for overseeing the dataset claimed that the dataset showed: “Climate change is supercharging many of these extremes that can lead to billion-dollar disasters” ( https://www.cbsnews.com/news/noaa-billion-dollar-weather-disasters-2022-hurricane-ian-drought/ ).

At the press conference where the 2022 dataset was released, the NOAA Administrator claimed that the dataset indicated that, “Climate change is creating more and more intense extreme events that cause significant damage” ( https://www.npr.org/2023/01/12/1148633707/extreme-weather-fueled-by-climate-change-cost-the-u-s-165-billion-in-2022 ).

In 2021 the U.S. Department of Treasury identified increasing billion dollar disasters as evidence of the effects of climate change on financial risks ( https://home.treasury.gov/system/files/261/FSOC-Climate-Report.pdf ).

The Fifth U.S. National Climate Assessment cited the NOAA dataset as evidence that “Climate change is not just a problem for future generations, it’s a problem today,” and claimed that the dataset, in part, demonstrated “the increasing frequency and severity of extreme events” due in part to “human-caused climate change” ( https://nca2023.globalchange.gov/chapter/2/ ).

In 2023, President Biden attributed weather and climate-related disaster costs in the U.S. in 2022 to climate change, citing the NOAA dataset: “[C]limate change related extreme weather events still pose a rapidly intensifying threat – one that costs the U.S. at least $150 billion each year … This year set a record for the number of climate disasters that cost the United States over $1 billion. The United States now experiences a billion-dollar disaster approximately every three weeks on average, compared to once every four months during the 1980s” ( https://www.whitehouse.gov/briefing-room/statements-releases/2023/11/14/fact-sheet-biden-harris-administration-releases-fifth-national-climate-assessment-and-announces-more-than-6-billion-to-strengthen-climate-resilience-across-the-country/ ).

The point here is not to call into question the reality or importance of human-caused climate change – it is real, and it is important. Rather, the question is whether the NOAA billion dollar disaster time series provides evidence of detection or attribution of changes in the climate of extreme weather events in the United States, as frequently claimed.

Economic loss data is not suitable for detection and attribution of trends in extreme weather events because losses involve more than just climatic factors. It is well understood that a disaster occurs at the intersection of an extreme event and a vulnerable and exposed society (IPCC) 8 . NOAA acknowledges that a combination of risk, vulnerability and exposure is necessary for a disaster to occur ( https://www.ncei.noaa.gov/access/billions/faq ), but it fails to take any of these factors into account in its methodologies prior to making claims of detection and attribution. Of note, NOAA performs such a GDP normalization for disasters at the state level but does not do so for its national billion dollar disaster database. In a June, 2023 insurance industry Webinar, the lead scientist responsible for the NOAA dataset identified the absence of a national GDP-based normalization to be a major challenge for interpreting the database, and suggested that this would be added to the dataset in the future ( https://www.catmanagers.org/event-details/put-past-losses-in-their-proper-context-1 ). Smith and Katz 7 explain that “the billion-dollar dataset is only adjusted for the CPI over time, not currently incorporating any changes in exposure (e.g., as reflected by shifts in wealth or population)”.

Over time, population and wealth have increased dramatically in the United States (and globally), meaning that when an extreme climate or weather event occurs, there is more to be damaged and invariably, more damage occurs even if there is no underlying trend in the frequency or intensity of extreme weather. Consequently, there is a large literature that seeks to “normalize” historical loss data to account for changes in exposure and vulnerability (e.g., a recent literature review identified more than 60 such papers 9 , other relevant studies discuss the importance of the spatial dimensions of land use change 10 , 11 , 12 , 13 ).

A common approach to disaster normalization adjusts historical losses based on GDP, as a proxy for increasing population and wealth 14 , 15 , 16 , 17 , 18 . Figure. 3 shows loss per disaster in the NOAA 2023 dataset as a percentage of US GDP ( https://fred.stlouisfed.org/series/RGDPNAUSA666NRUG ). According to a simple linear trend, losses per disaster are down by about 80% since 1980, as a proportion of GDP. This is likely due to a combination of actual decreasing losses as a proportion of GDP, as has been documented in many rich countries, as well as the sharp increase in small disasters included in NOAA’s dataset (see Fig. 2 ).

Losses per disaster in NOAA’s billion dollar disaster dataset (the version downloaded in July 2023), 1980 to 2022.

In comparison, weather and climate disasters losses as a percentage of U.S. GDP, show no increase over the period of record, which is 1990–2019 based on these data (Fig. 4 ).

Sources: Spatial Hazard Events and Losses Database for the United States (SHELDUS) at Arizona State University, which has made public aggregate losses from 1990 to 2019. Data on GDP from the U.S. Office of Management and Budget.

Other, more sophisticated and granular approaches to the normalization of U.S. weather and climate related disaster losses robustly confirm the aggregate downward trend in losses, once population growth and wealth are properly accounted 6 , 18 , 19 , 20 , 21 , 22 . Hurricane, flood and tornado losses have all decreased as a proportion of GDP on climate time scales, and as these are responsible for the majority of direct losses, so too have aggregate disaster losses.

NOAA’s failure to consider changes in exposure and vulnerability is significant. Consider for example Hurricane Andrew in 1992. The NOAA 2023 billion dollar disaster loss estimate for Andrew is $58.9 billion, but a 2023 normalized loss estimate is more than twice that at $119.9 billion (based on Weinkle et al.). For comparison, in 2022, Swiss Reinsurance estimated that a recurrence of Hurricane Andrew would result in $120 billion in total damage ( https://www.abcactionnews.com/news/price-of-paradise/experts-say-modern-day-hurricane-andrew-could-cost-florida-120-billion ). Thus, these estimates differ by ~100%.

By adjusting for inflation, but not for changes in exposure or vulnerability, the NOAA billion dollar dataset introduces a bias into the time series, as the upwards trend in losses in the billion dollar disaster time series is a result of growth in population and wealth, and not climate trends. As Smith and Katz 7 acknowledged more than a decade ago of the increase in billion dollar disasters, “the magnitude of such increasing trends is greatly diminished when applied to data normalized for exposure.”

Thus, any claim that the NOAA billion dollar disaster dataset indicates worsening weather or worsening disasters is incomplete at best and misleading at worst. When U.S. disaster losses are considered in the context of exposure changes it becomes clear that as the absolute costs of disasters has increased, the impact relative to the economy has diminished over past decades, which is exactly the opposite of claims made by NOAA, the U.S. National Climate Assessment, the USGCRP, and the president of the United States, among many others.

The most appropriate data for investigating detection and attribution of changes in climate variables will always be climate data, and not economic data. IPCC has assessed research on the detection and attribution of trends in extreme weather events and has only low confidence in the emergence of signals of climate-impact drivers for river floods, heavy precipitation and pluvial flood, landslide, drought, fire weather, tropical cyclones, hail, severe wind storms and heavy snowfall 2 – that is, each of the elements of the billion dollar disaster dataset. The IPCC does express confidence in some regions in the detection and attribution of changes in heat extremes and in extreme precipitation 2 , neither of which is an element of the billion dollar disaster database. The IPCC is explicit in warning against conflating changes in extreme precipitation with changes in pluvial flooding 2 .

NOAA makes strong claims of detection and attribution contrary to the conclusions of the IPCC but provides no analyses in support of these claims. For instance, NOAA states of its time series:

“The increases in population and material wealth over the last several decades are an important factor for higher damage potential. These trends are further complicated by the fact that many population centers and infrastructure exist in vulnerable areas like coasts and river floodplains, while building codes are often insufficient in reducing damage from extreme events. Climate change is also playing a role in the increasing frequency of some types of extreme weather that lead to billion-dollar disasters.”

However, NOAA makes no effort to quantify the roles of increasing population and material wealth, nor does it substantiate its claims that climate change has increased the frequency of some types of extreme weather.

NOAA does not acknowledge a large literature on disaster “normalization” that seeks to quantify the roles of population, material wealth, mitigation, building practices, etc. on increasing losses and also ignores literature on the detection and attribution of trends in various forms of extreme weather 2 , 9 .

Thus, any claim that the NOAA billion dollar disaster dataset indicates the detection trends in climate variables and the attribution of those trends to human-caused climate change is contrary to the most recent assessment of the IPCC. NOAA has provided no evidence or research to support claims that human-caused changes in climate are driving the increase in billion dollar disaster counts. Similarly, the opposite claim, that increasing billion dollar disasters are evidence of changes in the frequency of some extreme events resulting from human-caused climate change is also unsupported. NOAA’s claims are also circular – one claim is that climate change causes increasing billion dollar disasters and the second claim is that increasing billion dollar disasters indicate climate change. The billion dollar dataset fails to meet NOAA’s criteria of presentation and substance.

To summarize: the NOAA billion dollar disaster dataset falls short of NOAA’s guidelines for scientific integrity. The shortfalls documented here are neither small nor subtle. They represent a departure from NOAA’s long-term history of scientific integrity and excellence, which has saved countless lives and supported the nation’s economy.

Identifying the reasons why NOAA’s billion dollar disaster dataset has departed so significantly from the agency’s own standards of scientific integrity goes well beyond the scope of this paper. However, the steps necessary to bring the dataset back into conformance with NOAA’s information quality criteria are straightforward ( https://www.noaa.gov/organization/information-technology/policy-oversight/information-quality/information-quality-guidelines ):

Publish all data, including all versions of the dataset;

Document and publish baseline loss estimates and their provenance;

Clearly describe all methodologies employed to adjust baseline data;

Document every change made to the dataset, give each successive version of the dataset a unique name, and publish all version of the data;

Maintain all historical versions of the dataset in a publicly accessible archive;

Subject the methods and results to annual peer review by experts, including economists and others with subject matter expertise, who are independent of NOAA. Make the peer review reports public;

Align NOAA’s practices with federal government policies for disseminating statistical information that are applied to other agencies ( https://www.federalregister.gov/documents/2002/06/04/02-13892/federal-statistical-organizations-guidelines-for-ensuring-and-maximizing-the-quality-objectivity );

Align claims with IPCC methods and standards for any claims of detection and attribution, or justify why the claims are at odds with those of the IPCC.

NOAA is a crucially important agency that sits at the intersection of science, policy and politics. It has a long and distinguished history of providing weather, climate, water, ocean and other data to the nation. These data have saved countless lives, supported the economy and enabled significant scientific research. The agency is far too important to allow the shortfalls in scientific integrity documented in this paper to persist. Fortunately, science and policy are both self-correcting.

Policy evaluation

The analysis in this paper follows the logic of policy evaluation, which compares policy implementation with respect to criteria, with a goal of identifying progress or lack thereof towards goals (sources). Identifying progress requires identification of specific metrics of progress and data relevant to those metrics.

Lott, N. & Ross, T. Tracking and evaluating U.S. billion dollar disasters, 1980-2005, NOAA’s National Climatic Data Center, Asheville, North Carolina, https://www.ncei.noaa.gov/monitoring-content/billions/docs/lott-and-ross-2006.pdf (2005).

IPCC. Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [eds Masson-Delmotte, V., P et al.]. 2391 (Cambridge University Press, Cambridge, 2021) https://doi.org/10.1017/9781009157896 .

Pielke, R. Jr. & Boye, E. Scientific integrity and anti-doping regulation. Int. J. Sport Policy Polit. 11 , 295–313 (2019).

Article   Google Scholar  

Lasswell, H.D. A pre-view of policy sciences (Elsevier Publishing Company, 1971).

Smith, A. B. & Matthews, J. L. Quantifying uncertainty and variable sensitivity within the US billion-dollar weather and climate disaster cost estimates. Nat. Hazards 77 , 1829–1851 (2015).

Weinkle, J. et al. Normalized hurricane damage in the continental United States 1900–2017. Nat. Sustain. 1 , 808–813 (2018).

Smith, A. B. & Katz, R. W. US billion-dollar weather and climate disasters: data sources, trends, accuracy and biases. Nat. Hazards 67 , 387–410 (2013).

IPCC. Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (eds. Field, C.B. et al.) 582 (Cambridge University Press, 2012).

Pielke, R. Economic ‘normalisation’ of disaster losses 1998–2020: A literature review and assessment. Environ. Hazards 20 , 93–111 (2021).

Ye, M., Wu, J., Liu, W., He, X. & Wang, C. Dependence of tropical cyclone damage on maximum wind speed and socioeconomic factors. Environ. Res. Lett. 15 , 094061 (2020).

Strader, S. M., Ashley, W. S., Pingel, T. J. & Krmenec, A. J. How land use alters the tornado disaster landscape. Appl. Geogr. 94 , 18–29 (2018).

Ferguson, A. P. & Ashley, W. S. Spatiotemporal analysis of residential flood exposure in the Atlanta, Georgia metropolitan area. Nat. Hazards 87 , 989–1016 (2017).

Strader, S. M. & Ashley, W. S. The expanding bull’s-eye effect. Weatherwise 68 , 23–29 (2015).

Nordhaus, W. D. The economics of hurricanes and implications of global warming. Clim. Change Econ. 1 , 1–20 (2010).

Neumayer, E. & Barthel, F. Normalizing economic loss from natural disasters: A global analysis. Global Environ. Change 21 , 13–24 (2011).

Wu, J. et al. Post-disaster recovery and economic impact of catastrophes in China. Earthq. Spectra 30 , 1825–1846 (2014).

Chen, W., Lu, Y., Sun, S., Duan, Y. & Leckebusch, G. C. Hazard footprint-based normalization of economic losses from tropical cyclones in China during 1983–2015. Int. J. Disaster Risk Scie. 9 , 195–206 (2018).

Alstadt, B., Hanson, A. & Nijhuis, A. Developing a Global Method for Normalizing Economic Loss from Natural Disasters. Nat. Hazards Rev. 23 , 04021059 (2022).

Martinez, A. B. Improving normalized hurricane damages. Nat. Sustain. 3 , 517–518 (2020).

Klotzbach, P. J., Bowen, S. G., Pielke, R. & Bell, M. Continental US hurricane landfall frequency and associated damage: Observations and future risks. Bull. Am. Meteorol. Soc. 99 , 1359–1376 (2018).

Katz, R. W. Statistical issues in detection of trends in losses from extreme weather and climate events. In Evaluating climate change impact s. 165–186 (Chapman and Hall/CRC, 2020).

Zhang, J., Trück, S., Truong, C., & Pitt, D. Time trends in losses from major tornadoes in the United States. Weather Clim Extremes 41 , 100579 (2023).

Download references

Author information

Authors and affiliations.

University of Colorado Boulder, Boulder, CO, USA

Roger Pielke Jr

American Enterprise Institute, Washington, DC, USA

You can also search for this author in PubMed   Google Scholar

Contributions

R.P. did everything.

Corresponding author

Correspondence to Roger Pielke Jr .

Ethics declarations

Competing interests.

The author declares no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Pielke, R. Scientific integrity and U.S. “Billion Dollar Disasters”. npj Nat. Hazards 1 , 12 (2024). https://doi.org/10.1038/s44304-024-00011-0

Download citation

Received : 05 January 2024

Accepted : 13 April 2024

Published : 03 June 2024

DOI : https://doi.org/10.1038/s44304-024-00011-0

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing: Anthropocene newsletter — what matters in anthropocene research, free to your inbox weekly.

Numbers, Facts and Trends Shaping Your World

Read our research on:

Full Topic List

Regions & Countries

• Publications
• Our Methods
• Short Reads
• Tools & Resources

Read Our Research On:

Table of Contents

Which social media platforms are most common, who uses each social media platform, find out more, social media fact sheet.

Many Americans use social media to connect with one another, engage with news content, share information and entertain themselves. Explore the patterns and trends shaping the social media landscape.

To better understand Americans’ social media use, Pew Research Center surveyed 5,733 U.S. adults from May 19 to Sept. 5, 2023. Ipsos conducted this National Public Opinion Reference Survey (NPORS) for the Center using address-based sampling and a multimode protocol that included both web and mail. This way nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race and ethnicity, education and other categories.

Polls from 2000 to 2021 were conducted via phone. For more on this mode shift, read our Q&A.

Here are the questions used for this analysis , along with responses, and  its methodology ­­­.

A note on terminology: Our May-September 2023 survey was already in the field when Twitter changed its name to “X.” The terms  Twitter  and  X  are both used in this report to refer to the same platform.

YouTube and Facebook are the most-widely used online platforms. About half of U.S. adults say they use Instagram, and smaller shares use sites or apps such as TikTok, LinkedIn, Twitter (X) and BeReal.

Note: The vertical line indicates a change in mode. Polls from 2012-2021 were conducted via phone. In 2023, the poll was conducted via web and mail. For more details on this shift, please read our Q&A . Refer to the topline for more information on how question wording varied over the years. Pre-2018 data is not available for YouTube, Snapchat or WhatsApp; pre-2019 data is not available for Reddit; pre-2021 data is not available for TikTok; pre-2023 data is not available for BeReal. Respondents who did not give an answer are not shown.

Source: Surveys of U.S. adults conducted 2012-2023.

Usage of the major online platforms varies by factors such as age, gender and level of formal education.

% of U.S. adults who say they ever use __ by …

• RACE & ETHNICITY
• POLITICAL AFFILIATION

This fact sheet was compiled by Research Assistant  Olivia Sidoti , with help from Research Analyst  Risa Gelles-Watnick , Research Analyst  Michelle Faverio , Digital Producer  Sara Atske , Associate Information Graphics Designer Kaitlyn Radde and Temporary Researcher  Eugenie Park .

Follow these links for more in-depth analysis of the impact of social media on American life.

• Americans’ Social Media Use  Jan. 31, 2024
• Americans’ Use of Mobile Technology and Home Broadband  Jan. 31 2024
• Q&A: How and why we’re changing the way we study tech adoption  Jan. 31, 2024

Find more reports and blog posts related to  internet and technology .

1615 L St. NW, Suite 800 Washington, DC 20036 USA (+1) 202-419-4300 | Main (+1) 202-857-8562 | Fax (+1) 202-419-4372 |  Media Inquiries

Research Topics

• Email Newsletters

ABOUT PEW RESEARCH CENTER  Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of  The Pew Charitable Trusts .

© 2024 Pew Research Center

• Artificial Intelligence /

Perplexity will research and write reports

A new feature called pages will do the searching, writing, and laying out of a report with just a prompt..

By Emilia David , a reporter who covers AI. Prior to joining The Verge, she covered the intersection between technology, finance, and the economy.

Share this story

AI search platform Perplexity is launching a new feature called Pages that will generate a customizable webpage based on user prompts. The new feature feels like a one-stop shop for making a school report since Perplexity does the research and writing for you.

Pages taps Perplexity’s AI search models to find information and then creates what I can loosely call a research presentation that can be published and shared with others.  In a blog post , Perplexity says it designed Pages to help educators, researchers, and “hobbyists” share their knowledge.

Users type out what their report is about or what they want to know in the prompt box. They can gear the writing more toward beginners, expert readers, or a more general audience. Perplexity searches for information, then begins writing the page by breaking down the information into sections, citing some sources, and then adding visuals. Users can make the page as detailed or concise as they want, and they can also change the images Perplexity uses. However, you can’t edit the text it generates; you have to write another prompt to fix any mistakes.

I tried out Pages ahead of time to see how it works. Pages is not geared toward people like me who already have an avenue to share our knowledge. But it doesn’t seem geared toward researchers or teachers, either. I wanted to see how it can break down complex topics and if it can help with the difficult task of presenting dense information to different audiences.

Among other topics, I asked Perplexity’s Pages to generate a page on the “convergence of quantum computing and artificial intelligence and its impact on society” across the three audience types. The main difference between audiences seems to be the jargon in the written text and the kind of website it takes data from. Each generated report pulls from different sources, including introductory blog posts like this one from IBM . It also cited Wikipedia, which drove the student report vibe home.

The Perplexity-generated page did a passable job of explaining the basics of quantum computing and how AI fits into the technology. But the “research” didn’t go as deep as I could have if I were writing the presentation myself. The more advanced version didn’t even really talk about “the convergence of quantum computing and AI.” It found blog posts talking about quantum inflection points , which is when quantum technologies become more commercially viable and is not at all related to what I asked it to write about.

Then, I asked Pages to write a report about myself, mainly because the information there is easily verifiable. But it only took information from my personal website and an article about me on my high school’s website — not from other public, easily accessible sources like my author page on The Verge . It also sometimes elaborated on things that had nothing to do with me. For example, I began my journalism career during the 2008 financial crisis. Instead of talking about the pieces I wrote about mass layoffs, Perplexity explained the beginnings of the financial crisis.

Pages does the surface-level googling and writing for you, but it isn’t research. Perplexity claims that Pages will help educators develop “comprehensive” study guides for students and researchers to create detailed reports on their findings. I could not upload a research paper for it to summarize, and I couldn’t edit the text it generated, two things I believe users who want to make the most of Pages would appreciate.

I do see one potential user for Pages, and it isn’t one Perplexity called out: students rushing to put out an assignment. Pages may improve in the future. Right now, it’s a way to get easy, possibly correct surface-level information into a presentation that doesn’t really teach anything.

Pages will be available to all Perplexity users, and the company says it’s slowly rolling it out to its free, Pro, and Enterprise users. 

Tesla CEO Elon Musk could leave if $56 billion pay package not approved, shareholders warned

Humane warns ai pin owners to ‘immediately’ stop using its charging case, google makes its note-taking ai notebooklm more useful, netflix’s latest redesign aims to simplify your homepage, what’s next for xbox and halo.

More from Artificial Intelligence

Alexa’s Fire TV search has a new AI, but it needs some work

Anthropic’s AI now lets you create bots to work for you

Google Zero is here — now what?

Custom GPTs open for free ChatGPT users

Common Sense Media

Movie & TV reviews for parents

• For Parents
• For Educators
• Our Work and Impact
• Get the app
• Media Choice
• Digital Equity
• Digital Literacy and Citizenship
• Tech Accountability
• Healthy Childhood
• 20 Years of Impact

The Healthy Young Minds Campaign

AI Ratings and Reviews

• Our Current Research
• Past Research
• Archived Datasets

How Diverse Communities of Young People Think About Social Media and Mental Health

2023 State of Kids' Privacy

• Press Releases
• Our Experts
• Our Perspectives
• Public Filings and Letters

Common Sense Media Announces Framework for First-of-Its-Kind AI Ratings System

Protecting Kids' Digital Privacy Is Now Easier Than Ever

• How We Work
• Diversity and Inclusion
• Meet Our Team
• Board of Directors
• Board of Advisors
• Our Partners
• How We Rate and Review Media
• How We Rate and Review for Learning
• Our Offices
• Join as a Parent
• Join as an Educator
• Sign Up for Our Newsletters
• Request a Speaker
• We're Hiring

Teen and Young Adult Perspectives on Generative AI: Patterns of Use, Excitements, and Concerns

June 3, 2024

Generative artificial intelligence (AI) has quickly become an integral part of the digital landscape, surfacing new ways for people to learn, create, and innovate. At the same time, it brings both proven and unknown risks to everything from privacy to equity and accuracy.

Young people are extremely important in considering the future of generative AI—they're not only early adopters and influencers, but will also be among the first to grapple with its consequences. Understanding the perspectives of young people when it comes to generative AI is paramount, especially considering the impact of digital technologies on youth well-being.

This study, conducted in partnership with  Hopelab and the  Center for Digital Thriving at Harvard Graduate School of Education, examines how young people perceive and interact with generative AI technologies, with special attention to race and ethnicity, age, gender, and LGBTQ+ identity.

These nuanced views of teens and young adults from diverse demographic groups offer valuable insights into the potential benefits of generative AI, such as broader access to information, streamlining of tasks, and enhanced creativity. However, young people also expressed concerns about potential negative impacts, including job loss, privacy issues, intellectual property theft, misinformation and disinformation, and even AI taking over the world.

It's essential to understand young people's perspectives about generative AI, especially when considering programs, policies, and design features that impact the mental health of marginalized and minority populations like LGBTQ+, Black, and Latinx youth. The data in this report can ensure that the well-being of the earliest adopters is prioritized.

More resources:

See the press release .

Learn more about Common Sense's AI literacy lessons for grades 6-12.

Learn more about our AI Initiative, including previous research and our ratings for popular products.

Explore resources from our partners at Hopelab and the Center for Digital Thriving .

Types of Fat

Unsaturated fats

Unsaturated fats, which are liquid at room temperature, are considered beneficial fats because they can improve blood cholesterol levels, ease inflammation, stabilize heart rhythms, and play a number of other beneficial roles. Unsaturated fats are predominantly found in foods from plants, such as vegetable oils, nuts, and seeds.

There are two types of “good” unsaturated fats:

1. Monounsaturated fats are found in high concentrations in:

• Olive, peanut, and canola oils
• Nuts such as almonds, hazelnuts, and pecans
• Seeds such as pumpkin and sesame seeds

2. Polyunsaturated fats are found in high concentrations in

• Sunflower, corn, soybean, and flaxseed oils
• Canola oil – though higher in monounsaturated fat, it’s also a good source of polyunsaturated fat.

Omega-3 fats are an important  type of polyunsaturated fat. The body can’t make these, so they must come from food.

• An excellent way to get omega-3 fats is by eating fish 2-3 times a week.
• Good plant sources of omega-3 fats include flax seeds, walnuts, and canola or soybean oil.
• Higher blood omega-3 fats are associated with lower risk of premature death among older adults, according to a study by HSPH faculty.
• Read more about omega-3 fats in our Ask the Expert with Dr. Frank Sacks.

Most people don’t eat enough healthful unsaturated fats. The American Heart Association suggests that 8-10 percent of daily calories should come from polyunsaturated fats, and there is evidence that eating more polyunsaturated fat—up to 15 percent of daily calories—in place of saturated fat can lower heart disease risk. ( 7 )

• Dutch researchers conducted an analysis of 60 trials that examined the effects of carbohydrates and various fats on blood lipid levels. In trials in which polyunsaturated and monounsaturated fats were eaten in place of carbohydrates, these good fats decreased levels of harmful LDL and increased protective HDL. ( 8 )
• More recently, a randomized trial known as the Optimal Macronutrient Intake Trial for Heart Health (OmniHeart) showed that replacing a carbohydrate-rich diet with one rich in unsaturated fat, predominantly monounsaturated fats, lowers blood pressure, improves lipid levels, and reduces the estimated cardiovascular risk. ( 9 )

Finding Foods with Healthy Fats   is a handy visual guide to help you determine which fats are beneficial, and which are harmful.

Saturated Fats

All foods containing fat have a mix of specific types of fats. Even healthy foods like chicken and nuts have small amounts of saturated fat, though much less than the amounts found in beef, cheese, and ice cream. Saturated fat is mainly found in animal foods, but a few plant foods are also high in saturated fats, such as coconut, coconut oil , palm oil, and palm kernel oil.

• The Dietary Guidelines for Americans recommends getting less than 10 percent of calories each day from saturated fat. ( 10 )
• The American Heart Association goes even further, recommending limiting saturated fat to no more than 7 percent of calories. ( 11 )
• Cutting back on saturated fat will likely have no benefit, however, if people replace saturated fat with refined carbohydrates. Eating refined carbohydrates in place of saturated fat does lower “bad” LDL cholesterol, but it also lowers the “good” HDL cholesterol and increases triglycerides. The net effect is as bad for the heart as eating too much saturated fat.

In the United States, the biggest sources of saturated fat ( 12 ) in the diet are

• Pizza and cheese
• Whole and reduced fat milk, butter and dairy desserts
• Meat products (sausage, bacon, beef, hamburgers)
• Cookies and other grain-based desserts
• A variety of mixed fast food dishes

Though decades of dietary advice ( 13 , 14 ) suggested saturated fat was harmful, in recent years that idea has begun to evolve. Several studies suggest that eating diets high in saturated fat do not raise the risk of heart disease, with one report analyzing the findings of 21 studies that followed 350,000 people for up to 23 years.

• Investigators looked at the relationship between saturated fat intake and coronary heart disease (CHD), stroke, and cardiovascular disease (CVD). Their controversial conclusion: “There is insufficient evidence from prospective epidemiologic studies to conclude that dietary saturated fat is associated with an increased risk of CHD, stroke, or CVD.”( 13 )
• A well-publicized 2014 study questioned the link between saturated fat and heart disease, but HSPH nutrition experts determined the paper to be seriously misleading . In order to set the record straight, Harvard School of Public Health convened a panel of nutrition experts and held a teach-in, “ Saturated or not: Does type of fat matter? “

The overarching message is that cutting back on saturated fat can be good for health if people replace saturated fat with good fats , especially, polyunsaturated fats. ( 1 , 15 , 22 ) Eating good fats in place of saturated fat lowers the “bad” LDL cholesterol, and it improves the ratio of total cholesterol to “good” HDL cholesterol, lowering the risk of heart disease.

Eating good fats in place of saturated fat can also help prevent insulin resistance, a precursor to diabetes. ( 16 ) So while saturated fat may not be as harmful as once thought, evidence clearly shows that unsaturated fat remains the healthiest type of fat.

*Values expressed as percent of total fat; data are from analyses at Harvard School of Public Health Lipid Laboratory and U.S.D.A. publications.

Trans fatty acids, more commonly called trans fats, are made by heating liquid vegetable oils in the presence of hydrogen gas and a catalyst, a process called hydrogenation.

• Partially hydrogenating vegetable oils makes them more stable and less likely to become rancid. This process also converts the oil into a solid, which makes them function as margarine or shortening.
• Partially hydrogenated oils can withstand repeated heating without breaking down, making them ideal for frying fast foods.
• For these reasons, partially hydrogenated oils became a mainstay in restaurants and the food industry – for frying, baked goods, and processed snack foods and margarine.

Partially hydrogenated oil is not the only source of trans fats in our diets. Trans fats are also naturally found in beef fat and dairy fat in small amounts.

Trans fats are the worst type of fat for the heart, blood vessels, and rest of the body because they:

• Raise bad LDL and lower good HDL
• Create inflammation, ( 18 ) – a reaction related to immunity – which has been implicated in heart disease, stroke, diabetes, and other chronic conditions
• Contribute to insulin resistance ( 16 )
• Can have harmful health effects even in small amounts – for each additional 2 percent of calories from trans fat consumed daily, the risk of coronary heart disease increases by 23 percent.

The long road to phasing-out artificial trans fats

7. Mozaffarian, D., R. Micha, and S. Wallace, Effects on coronary heart disease of increasing polyunsaturated fat in place of saturated fat: a systematic review and meta-analysis of randomized controlled trials. PLoS Med , 2010. 7(3): p. e1000252.

8. Mensink, R.P., et al., Effects of dietary fatty acids and carbohydrates on the ratio of serum total to HDL cholesterol and on serum lipids and apolipoproteins: a meta-analysis of 60 controlled trials. Am J Clin Nutr , 2003. 77(5): p. 1146-55.

9. Appel, L.J., et al., Effects of protein, monounsaturated fat, and carbohydrate intake on blood pressure and serum lipids: results of the OmniHeart randomized trial. JAMA , 2005. 294(19): p. 2455-64.

10. U.S. Department of Agriculture, U.S.D.o.H.a.H.S., Washington, D.C.: U.S. Government Printing Office. Dietary Guidelines for Americans, 2010, 2010.

11. Lichtenstein, A.H., et al., Diet and lifestyle recommendations revision 2006: a scientific statement from the American Heart Association Nutrition Committee. Circulation , 2006. 114(1): p. 82-96.

12. Institute, N.C., Risk Factor Monitoring and Methods: Table 1. Top Food Sources of Saturated Fat among U.S. Population, 2005–2006. NHANES.

13. Siri-Tarino, P.W., et al., Meta-analysis of prospective cohort studies evaluating the association of saturated fat with cardiovascular disease. Am J Clin Nutr , 2010. 91(3): p. 535-46.

14. Micha, R. and D. Mozaffarian, Saturated fat and cardiometabolic risk factors, coronary heart disease, stroke, and diabetes: a fresh look at the evidence. Lipids , 2010. 45(10): p. 893-905.

15. Astrup, A., et al., The role of reducing intakes of saturated fat in the prevention of cardiovascular disease: where does the evidence stand in 2010? Am J Clin Nutr , 2011. 93(4): p. 684-8.

16. Riserus, U., W.C. Willett, and F.B. Hu, Dietary fats and prevention of type 2 diabetes. Prog Lipid Res , 2009. 48(1): p. 44-51.

18. Mozaffarian, D., et al., Dietary intake of trans fatty acids and systemic inflammation in women. Am J Clin Nutr, 2004. 79(4): p. 606-12.

22. Farvid MS, Ding M, Pan A, Sun Q, Chiuve SE, Steffen LM, Willett WC, Hu FB. Dietary Linoleic Acid and Risk of Coronary Heart Disease: A Systematic Review and Meta-Analysis of Prospective Cohort Studies. Circulation, 2014.

Terms of Use

The contents of this website are for educational purposes and are not intended to offer personal medical advice. You should seek the advice of your physician or other qualified health provider with any questions you may have regarding a medical condition. Never disregard professional medical advice or delay in seeking it because of something you have read on this website. The Nutrition Source does not recommend or endorse any products.