research title variables

Research Variables 101

Independent variables, dependent variables, control variables and more

By: Derek Jansen (MBA) | Expert Reviewed By: Kerryn Warren (PhD) | January 2023

If you’re new to the world of research, especially scientific research, you’re bound to run into the concept of variables , sooner or later. If you’re feeling a little confused, don’t worry – you’re not the only one! Independent variables, dependent variables, confounding variables – it’s a lot of jargon. In this post, we’ll unpack the terminology surrounding research variables using straightforward language and loads of examples .

Overview: Variables In Research

What (exactly) is a variable.

The simplest way to understand a variable is as any characteristic or attribute that can experience change or vary over time or context – hence the name “variable”. For example, the dosage of a particular medicine could be classified as a variable, as the amount can vary (i.e., a higher dose or a lower dose). Similarly, gender, age or ethnicity could be considered demographic variables, because each person varies in these respects.

Within research, especially scientific research, variables form the foundation of studies, as researchers are often interested in how one variable impacts another, and the relationships between different variables. For example:

• How someone’s age impacts their sleep quality
• How different teaching methods impact learning outcomes
• How diet impacts weight (gain or loss)

As you can see, variables are often used to explain relationships between different elements and phenomena. In scientific studies, especially experimental studies, the objective is often to understand the causal relationships between variables. In other words, the role of cause and effect between variables. This is achieved by manipulating certain variables while controlling others – and then observing the outcome. But, we’ll get into that a little later…

The “Big 3” Variables

Variables can be a little intimidating for new researchers because there are a wide variety of variables, and oftentimes, there are multiple labels for the same thing. To lay a firm foundation, we’ll first look at the three main types of variables, namely:

• Independent variables (IV)
• Dependant variables (DV)
• Control variables

What is an independent variable?

Simply put, the independent variable is the “ cause ” in the relationship between two (or more) variables. In other words, when the independent variable changes, it has an impact on another variable.

For example:

• Increasing the dosage of a medication (Variable A) could result in better (or worse) health outcomes for a patient (Variable B)
• Changing a teaching method (Variable A) could impact the test scores that students earn in a standardised test (Variable B)
• Varying one’s diet (Variable A) could result in weight loss or gain (Variable B).

It’s useful to know that independent variables can go by a few different names, including, explanatory variables (because they explain an event or outcome) and predictor variables (because they predict the value of another variable). Terminology aside though, the most important takeaway is that independent variables are assumed to be the “cause” in any cause-effect relationship. As you can imagine, these types of variables are of major interest to researchers, as many studies seek to understand the causal factors behind a phenomenon.

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What is a dependent variable?

While the independent variable is the “ cause ”, the dependent variable is the “ effect ” – or rather, the affected variable . In other words, the dependent variable is the variable that is assumed to change as a result of a change in the independent variable.

Keeping with the previous example, let’s look at some dependent variables in action:

• Health outcomes (DV) could be impacted by dosage changes of a medication (IV)
• Students’ scores (DV) could be impacted by teaching methods (IV)
• Weight gain or loss (DV) could be impacted by diet (IV)

In scientific studies, researchers will typically pay very close attention to the dependent variable (or variables), carefully measuring any changes in response to hypothesised independent variables. This can be tricky in practice, as it’s not always easy to reliably measure specific phenomena or outcomes – or to be certain that the actual cause of the change is in fact the independent variable.

As the adage goes, correlation is not causation . In other words, just because two variables have a relationship doesn’t mean that it’s a causal relationship – they may just happen to vary together. For example, you could find a correlation between the number of people who own a certain brand of car and the number of people who have a certain type of job. Just because the number of people who own that brand of car and the number of people who have that type of job is correlated, it doesn’t mean that owning that brand of car causes someone to have that type of job or vice versa. The correlation could, for example, be caused by another factor such as income level or age group, which would affect both car ownership and job type.

To confidently establish a causal relationship between an independent variable and a dependent variable (i.e., X causes Y), you’ll typically need an experimental design , where you have complete control over the environmen t and the variables of interest. But even so, this doesn’t always translate into the “real world”. Simply put, what happens in the lab sometimes stays in the lab!

As an alternative to pure experimental research, correlational or “ quasi-experimental ” research (where the researcher cannot manipulate or change variables) can be done on a much larger scale more easily, allowing one to understand specific relationships in the real world. These types of studies also assume some causality between independent and dependent variables, but it’s not always clear. So, if you go this route, you need to be cautious in terms of how you describe the impact and causality between variables and be sure to acknowledge any limitations in your own research.

What is a control variable?

In an experimental design, a control variable (or controlled variable) is a variable that is intentionally held constant to ensure it doesn’t have an influence on any other variables. As a result, this variable remains unchanged throughout the course of the study. In other words, it’s a variable that’s not allowed to vary – tough life 🙂

As we mentioned earlier, one of the major challenges in identifying and measuring causal relationships is that it’s difficult to isolate the impact of variables other than the independent variable. Simply put, there’s always a risk that there are factors beyond the ones you’re specifically looking at that might be impacting the results of your study. So, to minimise the risk of this, researchers will attempt (as best possible) to hold other variables constant . These factors are then considered control variables.

Some examples of variables that you may need to control include:

• Temperature
• Time of day
• Noise or distractions

Which specific variables need to be controlled for will vary tremendously depending on the research project at hand, so there’s no generic list of control variables to consult. As a researcher, you’ll need to think carefully about all the factors that could vary within your research context and then consider how you’ll go about controlling them. A good starting point is to look at previous studies similar to yours and pay close attention to which variables they controlled for.

Of course, you won’t always be able to control every possible variable, and so, in many cases, you’ll just have to acknowledge their potential impact and account for them in the conclusions you draw. Every study has its limitations , so don’t get fixated or discouraged by troublesome variables. Nevertheless, always think carefully about the factors beyond what you’re focusing on – don’t make assumptions!

Other types of variables

As we mentioned, independent, dependent and control variables are the most common variables you’ll come across in your research, but they’re certainly not the only ones you need to be aware of. Next, we’ll look at a few “secondary” variables that you need to keep in mind as you design your research.

• Moderating variables
• Mediating variables
• Confounding variables
• Latent variables

Let’s jump into it…

What is a moderating variable?

A moderating variable is a variable that influences the strength or direction of the relationship between an independent variable and a dependent variable. In other words, moderating variables affect how much (or how little) the IV affects the DV, or whether the IV has a positive or negative relationship with the DV (i.e., moves in the same or opposite direction).

For example, in a study about the effects of sleep deprivation on academic performance, gender could be used as a moderating variable to see if there are any differences in how men and women respond to a lack of sleep. In such a case, one may find that gender has an influence on how much students’ scores suffer when they’re deprived of sleep.

It’s important to note that while moderators can have an influence on outcomes , they don’t necessarily cause them ; rather they modify or “moderate” existing relationships between other variables. This means that it’s possible for two different groups with similar characteristics, but different levels of moderation, to experience very different results from the same experiment or study design.

What is a mediating variable?

Mediating variables are often used to explain the relationship between the independent and dependent variable (s). For example, if you were researching the effects of age on job satisfaction, then education level could be considered a mediating variable, as it may explain why older people have higher job satisfaction than younger people – they may have more experience or better qualifications, which lead to greater job satisfaction.

Mediating variables also help researchers understand how different factors interact with each other to influence outcomes. For instance, if you wanted to study the effect of stress on academic performance, then coping strategies might act as a mediating factor by influencing both stress levels and academic performance simultaneously. For example, students who use effective coping strategies might be less stressed but also perform better academically due to their improved mental state.

In addition, mediating variables can provide insight into causal relationships between two variables by helping researchers determine whether changes in one factor directly cause changes in another – or whether there is an indirect relationship between them mediated by some third factor(s). For instance, if you wanted to investigate the impact of parental involvement on student achievement, you would need to consider family dynamics as a potential mediator, since it could influence both parental involvement and student achievement simultaneously.

What is a confounding variable?

A confounding variable (also known as a third variable or lurking variable ) is an extraneous factor that can influence the relationship between two variables being studied. Specifically, for a variable to be considered a confounding variable, it needs to meet two criteria:

• It must be correlated with the independent variable (this can be causal or not)
• It must have a causal impact on the dependent variable (i.e., influence the DV)

Some common examples of confounding variables include demographic factors such as gender, ethnicity, socioeconomic status, age, education level, and health status. In addition to these, there are also environmental factors to consider. For example, air pollution could confound the impact of the variables of interest in a study investigating health outcomes.

Naturally, it’s important to identify as many confounding variables as possible when conducting your research, as they can heavily distort the results and lead you to draw incorrect conclusions . So, always think carefully about what factors may have a confounding effect on your variables of interest and try to manage these as best you can.

What is a latent variable?

Latent variables are unobservable factors that can influence the behaviour of individuals and explain certain outcomes within a study. They’re also known as hidden or underlying variables , and what makes them rather tricky is that they can’t be directly observed or measured . Instead, latent variables must be inferred from other observable data points such as responses to surveys or experiments.

For example, in a study of mental health, the variable “resilience” could be considered a latent variable. It can’t be directly measured , but it can be inferred from measures of mental health symptoms, stress, and coping mechanisms. The same applies to a lot of concepts we encounter every day – for example:

• Emotional intelligence
• Quality of life
• Business confidence
• Ease of use

One way in which we overcome the challenge of measuring the immeasurable is latent variable models (LVMs). An LVM is a type of statistical model that describes a relationship between observed variables and one or more unobserved (latent) variables. These models allow researchers to uncover patterns in their data which may not have been visible before, thanks to their complexity and interrelatedness with other variables. Those patterns can then inform hypotheses about cause-and-effect relationships among those same variables which were previously unknown prior to running the LVM. Powerful stuff, we say!

Let’s recap

In the world of scientific research, there’s no shortage of variable types, some of which have multiple names and some of which overlap with each other. In this post, we’ve covered some of the popular ones, but remember that this is not an exhaustive list .

To recap, we’ve explored:

• Independent variables (the “cause”)
• Dependent variables (the “effect”)
• Control variables (the variable that’s not allowed to vary)

If you’re still feeling a bit lost and need a helping hand with your research project, check out our 1-on-1 coaching service , where we guide you through each step of the research journey. Also, be sure to check out our free dissertation writing course and our collection of free, fully-editable chapter templates .

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• USC Libraries
• Research Guides

Organizing Your Social Sciences Research Paper

• Choosing a Title
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

The title summarizes the main idea or ideas of your study. A good title contains the fewest possible words needed to adequately describe the content and/or purpose of your research paper.

Importance of Choosing a Good Title

The title is the part of a paper that is read the most, and it is usually read first . It is, therefore, the most important element that defines the research study. With this in mind, avoid the following when creating a title:

• If the title is too long, this usually indicates there are too many unnecessary words. Avoid language, such as, "A Study to Investigate the...," or "An Examination of the...." These phrases are obvious and generally superfluous unless they are necessary to covey the scope, intent, or type of a study.
• On the other hand, a title which is too short often uses words which are too broad and, thus, does not tell the reader what is being studied. For example, a paper with the title, "African Politics" is so non-specific the title could be the title of a book and so ambiguous that it could refer to anything associated with politics in Africa. A good title should provide information about the focus and/or scope of your research study.
• In academic writing, catchy phrases or non-specific language may be used, but only if it's within the context of the study [e.g., "Fair and Impartial Jury--Catch as Catch Can"]. However, in most cases, you should avoid including words or phrases that do not help the reader understand the purpose of your paper.
• Academic writing is a serious and deliberate endeavor. Avoid using humorous or clever journalistic styles of phrasing when creating the title to your paper. Journalistic headlines often use emotional adjectives [e.g., incredible, amazing, effortless] to highlight a problem experienced by the reader or use "trigger words" or interrogative words like how, what, when, or why to persuade people to read the article or click on a link. These approaches are viewed as counter-productive in academic writing. A reader does not need clever or humorous titles to catch their attention because the act of reading research is assumed to be deliberate based on a desire to learn and improve understanding of the problem. In addition, a humorous title can merely detract from the seriousness and authority of your research. 
• Unlike everywhere else in a college-level social sciences research paper [except when using direct quotes in the text], titles do not have to adhere to rigid grammatical or stylistic standards. For example, it could be appropriate to begin a title with a coordinating conjunction [i.e., and, but, or, nor, for, so, yet] if it makes sense to do so and does not detract from the purpose of the study [e.g., "Yet Another Look at Mutual Fund Tournaments"] or beginning the title with an inflected form of a verb such as those ending in -ing [e.g., "Assessing the Political Landscape: Structure, Cognition, and Power in Organizations"].

Appiah, Kingsley Richard et al. “Structural Organisation of Research Article Titles: A Comparative Study of Titles of Business, Gynaecology and Law.” Advances in Language and Literary Studies 10 (2019); Hartley James. “To Attract or to Inform: What are Titles for?” Journal of Technical Writing and Communication 35 (2005): 203-213; Jaakkola, Maarit. “Journalistic Writing and Style.” In Oxford Research Encyclopedia of Communication . Jon F. Nussbaum, editor. (New York: Oxford University Press, 2018): https://oxfordre.com/communication.

Structure and Writing Style

The following parameters can be used to help you formulate a suitable research paper title:

• The purpose of the research
• The scope of the research
• The narrative tone of the paper [typically defined by the type of the research]
• The methods used to study the problem

The initial aim of a title is to capture the reader’s attention and to highlight the research problem under investigation.

Create a Working Title Typically, the final title you submit to your professor is created after the research is complete so that the title accurately captures what has been done . The working title should be developed early in the research process because it can help anchor the focus of the study in much the same way the research problem does. Referring back to the working title can help you reorient yourself back to the main purpose of the study if you find yourself drifting off on a tangent while writing. The Final Title Effective titles in research papers have several characteristics that reflect general principles of academic writing.

• Indicate accurately the subject and scope of the study,
• Rarely use abbreviations or acronyms unless they are commonly known,
• Use words that create a positive impression and stimulate reader interest,
• Use current nomenclature from the field of study,
• Identify key variables, both dependent and independent,
• Reveal how the paper will be organized,
• Suggest a relationship between variables which supports the major hypothesis,
• Is limited to 5 to 15 substantive words,
• Does not include redundant phrasing, such as, "A Study of," "An Analysis of" or similar constructions,
• Takes the form of a question or declarative statement,
• If you use a quote as part of the title, the source of the quote is cited [usually using an asterisk and footnote],
• Use correct grammar and capitalization with all first words and last words capitalized, including the first word of a subtitle. All nouns, pronouns, verbs, adjectives, and adverbs that appear between the first and last words of the title are also capitalized, and
• Rarely uses an exclamation mark at the end of the title.

The Subtitle Subtitles are frequently used in social sciences research papers because it helps the reader understand the scope of the study in relation to how it was designed to address the research problem. Think about what type of subtitle listed below reflects the overall approach to your study and whether you believe a subtitle is needed to emphasize the investigative parameters of your research.

1.  Explains or provides additional context , e.g., "Linguistic Ethnography and the Study of Welfare Institutions as a Flow of Social Practices: The Case of Residential Child Care Institutions as Paradoxical Institutions." [Palomares, Manuel and David Poveda.  Text & Talk: An Interdisciplinary Journal of Language, Discourse and Communication Studies 30 (January 2010): 193-212]

2.  Adds substance to a literary, provocative, or imaginative title or quote , e.g., "Listen to What I Say, Not How I Vote": Congressional Support for the President in Washington and at Home." [Grose, Christian R. and Keesha M. Middlemass. Social Science Quarterly 91 (March 2010): 143-167]

3.  Qualifies the geographic scope of the research , e.g., "The Geopolitics of the Eastern Border of the European Union: The Case of Romania-Moldova-Ukraine." [Marcu, Silvia. Geopolitics 14 (August 2009): 409-432]

4.  Qualifies the temporal scope of the research , e.g., "A Comparison of the Progressive Era and the Depression Years: Societal Influences on Predictions of the Future of the Library, 1895-1940." [Grossman, Hal B. Libraries & the Cultural Record 46 (2011): 102-128]

5.  Focuses on investigating the ideas, theories, or work of a particular individual , e.g., "A Deliberative Conception of Politics: How Francesco Saverio Merlino Related Anarchy and Democracy." [La Torre, Massimo. Sociologia del Diritto 28 (January 2001): 75 - 98]

6.  Identifies the methodology used , e.g. "Student Activism of the 1960s Revisited: A Multivariate Analysis Research Note." [Aron, William S. Social Forces 52 (March 1974): 408-414]

7.  Defines the overarching technique for analyzing the research problem , e.g., "Explaining Territorial Change in Federal Democracies: A Comparative Historical Institutionalist Approach." [ Tillin, Louise. Political Studies 63 (August 2015): 626-641.

With these examples in mind, think about what type of subtitle reflects the overall approach to your study. This will help the reader understand the scope of the study in relation to how it was designed to address the research problem.

Anstey, A. “Writing Style: What's in a Title?” British Journal of Dermatology 170 (May 2014): 1003-1004; Balch, Tucker. How to Compose a Title for Your Research Paper. Augmented Trader blog. School of Interactive Computing, Georgia Tech University; Bavdekar, Sandeep B. “Formulating the Right Title for a Research Article.” Journal of Association of Physicians of India 64 (February 2016); Choosing the Proper Research Paper Titles. AplusReports.com, 2007-2012; Eva, Kevin W. “Titles, Abstracts, and Authors.” In How to Write a Paper . George M. Hall, editor. 5th edition. (Oxford: John Wiley and Sons, 2013), pp. 33-41; Hartley James. “To Attract or to Inform: What are Titles for?” Journal of Technical Writing and Communication 35 (2005): 203-213; General Format. The Writing Lab and The OWL. Purdue University; Kerkut G.A. “Choosing a Title for a Paper.” Comparative Biochemistry and Physiology Part A: Physiology 74 (1983): 1; “Tempting Titles.” In Stylish Academic Writing . Helen Sword, editor. (Cambridge, MA: Harvard University Press, 2012), pp. 63-75; Nundy, Samiran, et al. “How to Choose a Title?” In How to Practice Academic Medicine and Publish from Developing Countries? A Practical Guide . Edited by Samiran Nundy, Atul Kakar, and Zulfiqar A. Bhutta. (Springer Singapore, 2022), pp. 185-192.

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Variables in Research | Types, Definiton & Examples

Introduction

What is a variable, what are the 5 types of variables in research, other variables in research.

Variables are fundamental components of research that allow for the measurement and analysis of data. They can be defined as characteristics or properties that can take on different values. In research design , understanding the types of variables and their roles is crucial for developing hypotheses , designing methods , and interpreting results .

This article outlines the the types of variables in research, including their definitions and examples, to provide a clear understanding of their use and significance in research studies. By categorizing variables into distinct groups based on their roles in research, their types of data, and their relationships with other variables, researchers can more effectively structure their studies and achieve more accurate conclusions.

A variable represents any characteristic, number, or quantity that can be measured or quantified. The term encompasses anything that can vary or change, ranging from simple concepts like age and height to more complex ones like satisfaction levels or economic status. Variables are essential in research as they are the foundational elements that researchers manipulate, measure, or control to gain insights into relationships, causes, and effects within their studies. They enable the framing of research questions, the formulation of hypotheses, and the interpretation of results.

Variables can be categorized based on their role in the study (such as independent and dependent variables ), the type of data they represent (quantitative or categorical), and their relationship to other variables (like confounding or control variables). Understanding what constitutes a variable and the various variable types available is a critical step in designing robust and meaningful research.

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Variables are crucial components in research, serving as the foundation for data collection , analysis , and interpretation . They are attributes or characteristics that can vary among subjects or over time, and understanding their types is essential for any study. Variables can be broadly classified into five main types, each with its distinct characteristics and roles within research.

This classification helps researchers in designing their studies, choosing appropriate measurement techniques, and analyzing their results accurately. The five types of variables include independent variables, dependent variables, categorical variables, continuous variables, and confounding variables. These categories not only facilitate a clearer understanding of the data but also guide the formulation of hypotheses and research methodologies.

Independent variables

Independent variables are foundational to the structure of research, serving as the factors or conditions that researchers manipulate or vary to observe their effects on dependent variables. These variables are considered "independent" because their variation does not depend on other variables within the study. Instead, they are the cause or stimulus that directly influences the outcomes being measured. For example, in an experiment to assess the effectiveness of a new teaching method on student performance, the teaching method applied (traditional vs. innovative) would be the independent variable.

The selection of an independent variable is a critical step in research design, as it directly correlates with the study's objective to determine causality or association. Researchers must clearly define and control these variables to ensure that observed changes in the dependent variable can be attributed to variations in the independent variable, thereby affirming the reliability of the results. In experimental research, the independent variable is what differentiates the control group from the experimental group, thereby setting the stage for meaningful comparison and analysis.

Dependent variables

Dependent variables are the outcomes or effects that researchers aim to explore and understand in their studies. These variables are called "dependent" because their values depend on the changes or variations of the independent variables.

Essentially, they are the responses or results that are measured to assess the impact of the independent variable's manipulation. For instance, in a study investigating the effect of exercise on weight loss, the amount of weight lost would be considered the dependent variable, as it depends on the exercise regimen (the independent variable).

The identification and measurement of the dependent variable are crucial for testing the hypothesis and drawing conclusions from the research. It allows researchers to quantify the effect of the independent variable , providing evidence for causal relationships or associations. In experimental settings, the dependent variable is what is being tested and measured across different groups or conditions, enabling researchers to assess the efficacy or impact of the independent variable's variation.

To ensure accuracy and reliability, the dependent variable must be defined clearly and measured consistently across all participants or observations. This consistency helps in reducing measurement errors and increases the validity of the research findings. By carefully analyzing the dependent variables, researchers can derive meaningful insights from their studies, contributing to the broader knowledge in their field.

Categorical variables

Categorical variables, also known as qualitative variables, represent types or categories that are used to group observations. These variables divide data into distinct groups or categories that lack a numerical value but hold significant meaning in research. Examples of categorical variables include gender (male, female, other), type of vehicle (car, truck, motorcycle), or marital status (single, married, divorced). These categories help researchers organize data into groups for comparison and analysis.

Categorical variables can be further classified into two subtypes: nominal and ordinal. Nominal variables are categories without any inherent order or ranking among them, such as blood type or ethnicity. Ordinal variables, on the other hand, imply a sort of ranking or order among the categories, like levels of satisfaction (high, medium, low) or education level (high school, bachelor's, master's, doctorate).

Understanding and identifying categorical variables is crucial in research as it influences the choice of statistical analysis methods. Since these variables represent categories without numerical significance, researchers employ specific statistical tests designed for a nominal or ordinal variable to draw meaningful conclusions. Properly classifying and analyzing categorical variables allow for the exploration of relationships between different groups within the study, shedding light on patterns and trends that might not be evident with numerical data alone.

Continuous variables

Continuous variables are quantitative variables that can take an infinite number of values within a given range. These variables are measured along a continuum and can represent very precise measurements. Examples of continuous variables include height, weight, temperature, and time. Because they can assume any value within a range, continuous variables allow for detailed analysis and a high degree of accuracy in research findings.

The ability to measure continuous variables at very fine scales makes them invaluable for many types of research, particularly in the natural and social sciences. For instance, in a study examining the effect of temperature on plant growth, temperature would be considered a continuous variable since it can vary across a wide spectrum and be measured to several decimal places.

When dealing with continuous variables, researchers often use methods incorporating a particular statistical test to accommodate a wide range of data points and the potential for infinite divisibility. This includes various forms of regression analysis, correlation, and other techniques suited for modeling and analyzing nuanced relationships between variables. The precision of continuous variables enhances the researcher's ability to detect patterns, trends, and causal relationships within the data, contributing to more robust and detailed conclusions.

Confounding variables

Confounding variables are those that can cause a false association between the independent and dependent variables, potentially leading to incorrect conclusions about the relationship being studied. These are extraneous variables that were not considered in the study design but can influence both the supposed cause and effect, creating a misleading correlation.

Identifying and controlling for a confounding variable is crucial in research to ensure the validity of the findings. This can be achieved through various methods, including randomization, stratification, and statistical control. Randomization helps to evenly distribute confounding variables across study groups, reducing their potential impact. Stratification involves analyzing the data within strata or layers that share common characteristics of the confounder. Statistical control allows researchers to adjust for the effects of confounders in the analysis phase.

Properly addressing confounding variables strengthens the credibility of research outcomes by clarifying the direct relationship between the dependent and independent variables, thus providing more accurate and reliable results.

Beyond the primary categories of variables commonly discussed in research methodology , there exists a diverse range of other variables that play significant roles in the design and analysis of studies. Below is an overview of some of these variables, highlighting their definitions and roles within research studies:

• Discrete variables : A discrete variable is a quantitative variable that represents quantitative data , such as the number of children in a family or the number of cars in a parking lot. Discrete variables can only take on specific values.
• Categorical variables : A categorical variable categorizes subjects or items into groups that do not have a natural numerical order. Categorical data includes nominal variables, like country of origin, and ordinal variables, such as education level.
• Predictor variables : Often used in statistical models, a predictor variable is used to forecast or predict the outcomes of other variables, not necessarily with a causal implication.
• Outcome variables : These variables represent the results or outcomes that researchers aim to explain or predict through their studies. An outcome variable is central to understanding the effects of predictor variables.
• Latent variables : Not directly observable, latent variables are inferred from other, directly measured variables. Examples include psychological constructs like intelligence or socioeconomic status.
• Composite variables : Created by combining multiple variables, composite variables can measure a concept more reliably or simplify the analysis. An example would be a composite happiness index derived from several survey questions .
• Preceding variables : These variables come before other variables in time or sequence, potentially influencing subsequent outcomes. A preceding variable is crucial in longitudinal studies to determine causality or sequences of events.

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• Types of Variables in Research | Definitions & Examples

Types of Variables in Research | Definitions & Examples

Published on 19 September 2022 by Rebecca Bevans . Revised on 28 November 2022.

In statistical research, a variable is defined as an attribute of an object of study. Choosing which variables to measure is central to good experimental design .

You need to know which types of variables you are working with in order to choose appropriate statistical tests and interpret the results of your study.

You can usually identify the type of variable by asking two questions:

• What type of data does the variable contain?
• What part of the experiment does the variable represent?

Table of contents

Types of data: quantitative vs categorical variables, parts of the experiment: independent vs dependent variables, other common types of variables, frequently asked questions about variables.

Data is a specific measurement of a variable – it is the value you record in your data sheet. Data is generally divided into two categories:

• Quantitative data represents amounts.
• Categorical data represents groupings.

A variable that contains quantitative data is a quantitative variable ; a variable that contains categorical data is a categorical variable . Each of these types of variable can be broken down into further types.

Quantitative variables

When you collect quantitative data, the numbers you record represent real amounts that can be added, subtracted, divided, etc. There are two types of quantitative variables: discrete and continuous .

Categorical variables

Categorical variables represent groupings of some kind. They are sometimes recorded as numbers, but the numbers represent categories rather than actual amounts of things.

There are three types of categorical variables: binary , nominal , and ordinal variables.

*Note that sometimes a variable can work as more than one type! An ordinal variable can also be used as a quantitative variable if the scale is numeric and doesn’t need to be kept as discrete integers. For example, star ratings on product reviews are ordinal (1 to 5 stars), but the average star rating is quantitative.

Example data sheet

To keep track of your salt-tolerance experiment, you make a data sheet where you record information about the variables in the experiment, like salt addition and plant health.

To gather information about plant responses over time, you can fill out the same data sheet every few days until the end of the experiment. This example sheet is colour-coded according to the type of variable: nominal , continuous , ordinal , and binary .

Prevent plagiarism, run a free check.

Experiments are usually designed to find out what effect one variable has on another – in our example, the effect of salt addition on plant growth.

You manipulate the independent variable (the one you think might be the cause ) and then measure the dependent variable (the one you think might be the effect ) to find out what this effect might be.

You will probably also have variables that you hold constant ( control variables ) in order to focus on your experimental treatment.

In this experiment, we have one independent and three dependent variables.

The other variables in the sheet can’t be classified as independent or dependent, but they do contain data that you will need in order to interpret your dependent and independent variables.

What about correlational research?

When you do correlational research , the terms ‘dependent’ and ‘independent’ don’t apply, because you are not trying to establish a cause-and-effect relationship.

However, there might be cases where one variable clearly precedes the other (for example, rainfall leads to mud, rather than the other way around). In these cases, you may call the preceding variable (i.e., the rainfall) the predictor variable and the following variable (i.e., the mud) the outcome variable .

Once you have defined your independent and dependent variables and determined whether they are categorical or quantitative, you will be able to choose the correct statistical test .

But there are many other ways of describing variables that help with interpreting your results. Some useful types of variable are listed below.

A confounding variable is closely related to both the independent and dependent variables in a study. An independent variable represents the supposed cause , while the dependent variable is the supposed effect . A confounding variable is a third variable that influences both the independent and dependent variables.

Failing to account for confounding variables can cause you to wrongly estimate the relationship between your independent and dependent variables.

Discrete and continuous variables are two types of quantitative variables :

• Discrete variables represent counts (e.g., the number of objects in a collection).
• Continuous variables represent measurable amounts (e.g., water volume or weight).

You can think of independent and dependent variables in terms of cause and effect: an independent variable is the variable you think is the cause , while a dependent variable is the effect .

In an experiment, you manipulate the independent variable and measure the outcome in the dependent variable. For example, in an experiment about the effect of nutrients on crop growth:

• The  independent variable  is the amount of nutrients added to the crop field.
• The  dependent variable is the biomass of the crops at harvest time.

Defining your variables, and deciding how you will manipulate and measure them, is an important part of experimental design .

Cite this Scribbr article

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Organizing Academic Research Papers: Choosing a Title

• Purpose of Guide
• Design Flaws to Avoid
• Glossary of Research Terms
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Choosing a Title
• Making an Outline
• Paragraph Development
• Executive Summary
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tertiary Sources
• What Is Scholarly vs. Popular?
• Qualitative Methods
• Quantitative Methods
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Annotated Bibliography
• Dealing with Nervousness
• Using Visual Aids
• Grading Someone Else's Paper
• How to Manage Group Projects
• Multiple Book Review Essay
• Reviewing Collected Essays
• About Informed Consent
• Writing Field Notes
• Writing a Policy Memo
• Writing a Research Proposal
• Acknowledgements

The title summarizes the main idea or ideas of your study. A good title contains the fewest possible words that adequately describe the contents and/or purpose of your research paper.

The title is without doubt the part of a paper that is read the most, and it is usually read first . If the title is too long it usually contains too many unnecessary words, e.g., "A Study to Investigate the...." On the other hand, a title which is too short often uses words which are too general. For example, "African Politics" could be the title of a book, but it does not provide any information on the focus of a research paper.

Structure and Writing Style

The following parameters can be used to help you formulate a suitable research paper title:

• The purpose of the research
• The narrative tone of the paper [typically defined by the type of the research]
• The methods used

The initial aim of a title is to capture the reader’s attention and to draw his or her attention to the research problem being investigated.

Create a Working Title Typically, the final title you submit to your professor is created after the research is complete so that the title accurately captures what was done . The working title should be developed early in the research process because it can help anchor the focus of the study in much the same way the research problem does. Referring back to the working title can help you reorient yourself back to the main purpose of the study if you feel yourself drifting off on a tangent while writing. The Final Title Effective titles in academic research papers have several characteristics.

• Indicate accurately the subject and scope of the study.
• Avoid using abbreviations.
• Use words that create a positive impression and stimulate reader interest.
• Use current nomenclature from the field of study.
• Identify key variables, both dependent and independent.
• May reveal how the paper will be organized.
• Suggest a relationship between variables which supports the major hypothesis.
• Is limited to 10 to 15 substantive words.
• Do not include "study of," "analysis of" or similar constructions.
• Titles are usually in the form of a phrase, but can also be in the form of a question.
• Use correct grammar and capitalization with all first words and last words capitalized, including the first word of a subtitle. All nouns,  pronouns, verbs, adjectives, and adverbs that appear between the first and last words of the title are also capitalized.
• In academic papers, rarely is a title followed by an exclamation mark. However, a title or subtitle can be in the form of a question.

The Subtitle Subtitles are quite common in social science research papers. Examples of why you may include a subtitle:

• Explains or provides additional context , e.g., "Linguistic Ethnography and the Study of Welfare Institutions as a Flow of Social Practices: The Case of Residential Child Care Institutions as Paradoxical Institutions."
• Adds substance to a literary, provocative, or imaginative title , e.g., "Listen to What I Say, Not How I Vote: Congressional Support for the President in Washington and at Home."
• Qualifies the geographic scope of the research , e.g., "The Geopolitics of the Eastern Border of the European Union: The Case of Romania-Moldova-Ukraine."
• Qualifies the temporal scope of the research , e.g., "A Comparison of the Progressive Era and the Depression Years: Societal Influences on Predictions of the Future of the Library, 1895-1940."
• Focuses on investigating the ideas, theories, or work of a particular individual , e.g., "A Deliberative Conception of Politics: How Francesco Saverio Merlino Related Anarchy and Democracy."

Balch, Tucker. How to Compose a Title for Your Research Paper . Augmented Trader blog. School of Interactive Computing, Georgia Tech University;  Choosing the Proper Research Paper Titles . AplusReports.com, 2007-2012; General Format. The Writing Lab and The OWL. Purdue University.

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Independent and Dependent Variables

This guide discusses how to identify independent and dependent variables effectively and incorporate their description within the body of a research paper.

A variable can be anything you might aim to measure in your study, whether in the form of numerical data or reflecting complex phenomena such as feelings or reactions. Dependent variables change due to the other factors measured, especially if a study employs an experimental or semi-experimental design. Independent variables are stable: they are both presumed causes and conditions in the environment or milieu being manipulated.

Identifying Independent and Dependent Variables

Even though the definitions of the terms independent and dependent variables may appear to be clear, in the process of analyzing data resulting from actual research, identifying the variables properly might be challenging. Here is a simple rule that you can apply at all times: the independent variable is what a researcher changes, whereas the dependent variable is affected by these changes. To illustrate the difference, a number of examples are provided below.

• The purpose of Study 1 is to measure the impact of different plant fertilizers on how many fruits apple trees bear. Independent variable : plant fertilizers (chosen by researchers) Dependent variable : fruits that the trees bear (affected by choice of fertilizers)
• The purpose of Study 2 is to find an association between living in close vicinity to hydraulic fracturing sites and respiratory diseases. Independent variable: proximity to hydraulic fracturing sites (a presumed cause and a condition of the environment) Dependent variable: the percentage/ likelihood of suffering from respiratory diseases

Confusion is possible in identifying independent and dependent variables in the social sciences. When considering psychological phenomena and human behavior, it can be difficult to distinguish between cause and effect. For example, the purpose of Study 3 is to establish how tactics for coping with stress are linked to the level of stress-resilience in college students. Even though it is feasible to speculate that these variables are interdependent, the following factors should be taken into account in order to clearly define which variable is dependent and which is interdependent.

• The dependent variable is usually the objective of the research. In the study under examination, the levels of stress resilience are being investigated.
• The independent variable precedes the dependent variable. The chosen stress-related coping techniques help to build resilience; thus, they occur earlier.

Writing Style and Structure

Usually, the variables are first described in the introduction of a research paper and then in the method section. No strict guidelines for approaching the subject exist; however, academic writing demands that the researcher make clear and concise statements. It is only reasonable not to leave readers guessing which of the variables is dependent and which is independent. The description should reflect the literature review, where both types of variables are identified in the context of the previous research. For instance, in the case of Study 3, a researcher would have to provide an explanation as to the meaning of stress resilience and coping tactics.

In properly organizing a research paper, it is essential to outline and operationalize the appropriate independent and dependent variables. Moreover, the paper should differentiate clearly between independent and dependent variables. Finding the dependent variable is typically the objective of a study, whereas independent variables reflect influencing factors that can be manipulated. Distinguishing between the two types of variables in social sciences may be somewhat challenging as it can be easy to confuse cause with effect. Academic format calls for the author to mention the variables in the introduction and then provide a detailed description in the method section.

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How to write a good research paper title

“Unread science is lost science .”

Credit: Mykyta Dolmatov/Getty

“Unread science is lost science.”

28 July 2020

Mykyta Dolmatov/Getty

With the influx of publications brought on by the pandemic, it’s become more challenging than ever for researchers to attract attention to their work.

Understanding which elements of a title will attract readers – or turn them away – has been proven to increase a paper’s citations and Altmetric score .

“In the era of information overload, most students and researchers do not have time to browse the entire text of a paper,” says Patrick Pu , a librarian at the National University of Singapore.

“The title of a paper, together with its abstract, become very important to capture and sustain the attention of readers.”

1. A good title avoids technical language

Since the primary audience of a paper is likely to be researchers working in the same field, using technical language in the title seems to make sense.

But this alienates the wider lay audience, which can bring valuable attention to your work . It can also alienate inexperienced researchers, or those who have recently entered the field.

“A good title does not use unnecessary jargon,” says Elisa De Ranieri , editor-in-chief at the Nature Communications journal (published by Springer Nature, which also publishes Nature Index.) “It communicates the main results in the study in a way that is clear and accessible, ideally to non-specialists or researchers new to the field.”

How-to: When crafting a title, says De Ranieri, write down the main result of the manuscript in a short paragraph. Shorten the text to make it more concise, while still remaining descriptive. Repeat this process until you have a title of fewer than 15 words.

2. A good title is easily searchable

Most readers today are accessing e-journals, which are indexed in scholarly databases such as Scopus and Google Scholar.

“Although these databases usually index the full text of papers, retrieval weightage for ‘Title’ is usually higher than other fields, such as ‘Results’,” Pu explains.

At the National University of Singapore, Pu and his colleagues run information literacy programmes for editors and authors. They give advice for publishing best practice, such as how to identify the most commonly used keywords in literature searches in a given field.

“A professor once told us how he discovered that industry experts were using a different term or keyword to describe his research area,” says Pu.

“He had written a seminal paper that did not include this ‘industry keyword’. He believes his paper, which was highly cited by academics, would have a higher citation count if he had included this keyword in the title. As librarians, we try to highlight this example to our students so that they will consider all possible keywords to use in their searches and paper titles.”

How-to: Authors should speak to an academic librarian at their institution to gain an understanding of keyword and search trends in their field of research. This should inform how the paper title is written.

3. A good title is substantiated by data

Authors should be cautious to not make any claims in the title that can’t be backed up by evidence.

“For instance, if you make a discovery with potential therapeutic relevance, the title should specify whether it was tested or studied in animals or humans/human samples,” says Irene Jarchum , senior editor at the journal Nature Biotechnology (also published by Springer Nature, which publishes the Nature Index.)

Jarchum adds that titles can be contentious because different authors have different views on the use of specific words, such as acronyms, or more fundamentally, what the main message of the title should be.

Some authors may over-interpret the significance of their preliminary findings, and want to reflect this in the title.

How-to: If you know your paper will be contentious within the scientific community, have the data ready to defend your decisions .

4. A good title sparks curiosity

A one-liner that sparks a reader’s interest can be very effective.

“A title has to pique the interest of the person searching for literature in a split-second – enough that they click on the title to read the abstract. Unread science is lost science,” says Christine Mayer , editor-in-chief of the journal Advanced Therapeutics .

Paper titles such as, "White and wonderful? Microplastics prevail in snow from the Alps to the Arctic" ( 2019 Science ), and “Kids these days: Why the youth of today seem lacking” ( 2019 Science Advances ) are good examples of this principle. Both papers have high Altmetric Attention scores, indicating that they have been widely read and discussed online.

How-to: Take note of the characteristics of paper titles that spark your own interest. Keep a record of these and apply the same principles to your own paper titles.

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How to Make a Research Paper Title with Examples

What is a research paper title and why does it matter?

A research paper title summarizes the aim and purpose of your research study. Making a title for your research is one of the most important decisions when writing an article to publish in journals. The research title is the first thing that journal editors and reviewers see when they look at your paper and the only piece of information that fellow researchers will see in a database or search engine query. Good titles that are concise and contain all the relevant terms have been shown to increase citation counts and Altmetric scores .

Therefore, when you title research work, make sure it captures all of the relevant aspects of your study, including the specific topic and problem being investigated. It also should present these elements in a way that is accessible and will captivate readers. Follow these steps to learn how to make a good research title for your work.

How to Make a Research Paper Title in 5 Steps

You might wonder how you are supposed to pick a title from all the content that your manuscript contains—how are you supposed to choose? What will make your research paper title come up in search engines and what will make the people in your field read it? 

In a nutshell, your research title should accurately capture what you have done, it should sound interesting to the people who work on the same or a similar topic, and it should contain the important title keywords that other researchers use when looking for literature in databases. To make the title writing process as simple as possible, we have broken it down into 5 simple steps.

Step 1: Answer some key questions about your research paper

What does your paper seek to answer and what does it accomplish? Try to answer these questions as briefly as possible. You can create these questions by going through each section of your paper and finding the MOST relevant information to make a research title.

Step 2: Identify research study keywords

Now that you have answers to your research questions, find the most important parts of these responses and make these your study keywords. Note that you should only choose the most important terms for your keywords–journals usually request anywhere from 3 to 8 keywords maximum.

Step 3: Research title writing: use these keywords

“We employed a case study of 60 liver transplant patients around the US aged 20-50 years to assess how waiting list volume affects the outcomes of liver transplantation in patients; results indicate a positive correlation between increased waiting list volume and negative prognosis after the transplant procedure.”

The sentence above is clearly much too long for a research paper title. This is why you will trim and polish your title in the next two steps.

Step 4: Create a working research paper title

To create a working title, remove elements that make it a complete “sentence” but keep everything that is important to what the study is about. Delete all unnecessary and redundant words that are not central to the study or that researchers would most likely not use in a database search.

“ We employed a case study of 60 liver transplant patients around the US aged 20-50 years to assess how the waiting list volume affects the outcome of liver transplantation in patients ; results indicate a positive correlation between increased waiting list volume and a negative prognosis after transplant procedure ”

Now shift some words around for proper syntax and rephrase it a bit to shorten the length and make it leaner and more natural. What you are left with is:

“A case study of 60 liver transplant patients around the US aged 20-50 years assessing the impact of waiting list volume on outcome of transplantation and showing a positive correlation between increased waiting list volume and a negative prognosis” (Word Count: 38)

This text is getting closer to what we want in a research title, which is just the most important information. But note that the word count for this working title is still 38 words, whereas the average length of published journal article titles is 16 words or fewer. Therefore, we should eliminate some words and phrases that are not essential to this title.

Step 5: Remove any nonessential words and phrases from your title

Because the number of patients studied and the exact outcome are not the most essential parts of this paper, remove these elements first:

 “A case study of 60 liver transplant patients around the US aged 20-50 years assessing the impact of waiting list volume on outcomes of transplantation and showing a positive correlation between increased waiting list volume and a negative prognosis” (Word Count: 19)

In addition, the methods used in a study are not usually the most searched-for keywords in databases and represent additional details that you may want to remove to make your title leaner. So what is left is:

“Assessing the impact of waiting list volume on outcome and prognosis in liver transplantation patients” (Word Count: 15)

In this final version of the title, one can immediately recognize the subject and what objectives the study aims to achieve. Note that the most important terms appear at the beginning and end of the title: “Assessing,” which is the main action of the study, is placed at the beginning; and “liver transplantation patients,” the specific subject of the study, is placed at the end.

This will aid significantly in your research paper title being found in search engines and database queries, which means that a lot more researchers will be able to locate your article once it is published. In fact, a 2014 review of more than 150,000 papers submitted to the UK’s Research Excellence Framework (REF) database found the style of a paper’s title impacted the number of citations it would typically receive. In most disciplines, articles with shorter, more concise titles yielded more citations.

Adding a Research Paper Subtitle

If your title might require a subtitle to provide more immediate details about your methodology or sample, you can do this by adding this information after a colon:

“ : a case study of US adult patients ages 20-25”

If we abide strictly by our word count rule this may not be necessary or recommended. But every journal has its own standard formatting and style guidelines for research paper titles, so it is a good idea to be aware of the specific journal author instructions , not just when you write the manuscript but also to decide how to create a good title for it.

Research Paper Title Examples

The title examples in the following table illustrate how a title can be interesting but incomplete, complete by uninteresting, complete and interesting but too informal in tone, or some other combination of these. A good research paper title should meet all the requirements in the four columns below.

Tips on Formulating a Good Research Paper Title

In addition to the steps given above, there are a few other important things you want to keep in mind when it comes to how to write a research paper title, regarding formatting, word count, and content:

• Write the title after you’ve written your paper and abstract
• Include all of the essential terms in your paper
• Keep it short and to the point (~16 words or fewer)
• Avoid unnecessary jargon and abbreviations
• Use keywords that capture the content of your paper
• Never include a period at the end—your title is NOT a sentence

Research Paper Writing Resources

We hope this article has been helpful in teaching you how to craft your research paper title. But you might still want to dig deeper into different journal title formats and categories that might be more suitable for specific article types or need help with writing a cover letter for your manuscript submission.

In addition to getting English proofreading services , including paper editing services , before submission to journals, be sure to visit our academic resources papers. Here you can find dozens of articles on manuscript writing, from drafting an outline to finding a target journal to submit to.

6 Important Tips on Writing a Research Paper Title

When you are searching for a research study on a particular topic, you probably notice that articles with interesting, descriptive research titles draw you in. By contrast, research paper titles that are not descriptive are usually passed over, even though you may write a good research paper with interesting contents. This shows the importance of coming up with a good title for your research paper when drafting your own manuscript.

Importance of a Research Title

The research title plays a crucial role in the research process, and its importance can be summarized as follows:

Why do Research Titles Matter?

Before we look at how to title a research paper, let’s look at a research title example that illustrates why a good research paper should have a strong title.

Imagine that you are researching meditation and nursing, and you want to find out if any studies have shown that meditation makes nurses better communicators.  You conduct a keyword search using the keywords “nursing”, “communication”, and “meditation.” You come up with results that have the following titles:

• Benefits of Meditation for the Nursing Profession: A Quantitative Investigation
• Why Mindful Nurses Make the Best Communicators
• Meditation Gurus
• Nurses on the Move: A Quantitative Report on How Meditation Can Improve Nurse Performance

All four of these research paper titles may describe very similar studies—they could even be titles for the same study! As you can see, they give very different impressions.

• Title 1 describes the topic and the method of the study but is not particularly catchy.
• Title 2 partly describes the topic, but does not give any information about the method of the study—it could simply be a theoretical or opinion piece.
• Title 3 is somewhat catchier but gives almost no information at all about the article.
• Title 4 begins with a catchy main title and is followed by a subtitle that gives information about the content and method of the study.

As we will see, Title 4 has all the characteristics of a good research title.

Characteristics of a Good Research Title

According to rhetoric scholars Hairston and Keene, making a good title for a paper involves ensuring that the title of the research accomplishes four goals as mentioned below:

• It should predict the content of the research paper .
• It should be interesting to the reader .
• It should reflect the tone of the writing .
• It should contain important keywords that will make it easier to be located during a keyword search.

Let’s return to the examples in the previous section to see how to make a research title.

As you can see in the table above, only one of the four example titles fulfills all of the criteria of a suitable research paper title.

Related: You’ve chosen your study topic, but having trouble deciding where to publish it? Here’s a comprehensive course to help you identify the right journal .

Tips for Writing an Effective Research Paper Title

When writing a research title, you can use the four criteria listed above as a guide. Here are a few other tips you can use to make sure your title will be part of the recipe for an effective research paper :

• Make sure your research title describes (a) the topic, (b) the method, (c) the sample, and (d) the results of your study. You can use the following formula:

[ Result ]: A [ method ] study of [ topic ] among [ sample ] Example : Meditation makes nurses perform better: a qualitative study of mindfulness meditation among German nursing students

• Avoid unnecessary words and jargons. Keep the title statement as concise as possible. You want a title that will be comprehensible even to people who are not experts in your field. Check our article for a detailed list of things to avoid when writing an effective research title .
• Make sure your title is between 5 and 15 words in length.
• If you are writing a title for a university assignment or for a particular academic journal, verify that your title conforms to the standards and requirements for that outlet. For example, many journals require that titles fall under a character limit, including spaces. Many universities require that titles take a very specific form, limiting your creativity.
• Use a descriptive phrase to convey the purpose of your research efficiently.
• Most importantly, use critical keywords in the title to increase the discoverability of your article.

Resources for Further Reading

In addition to the tips above, there are many resources online that you can use to help write your research title. Here is a list of links that you may find useful as you work on creating an excellent research title:

• The University of Southern California has a guide specific to social science research papers: http://libguides.usc.edu/writingguide/title
• The Journal of European Psychology Students has a blog article focusing on APA-compliant research paper titles: http://blog.efpsa.org/2012/09/01/how-to-write-a-good-title-for-journal-articles/
• This article by Kristen Hamlin contains a step-by-step approach to writing titles: http://classroom.synonym.com/choose-title-research-paper-4332.html

Are there any tips or tricks you find useful in crafting research titles? Which tip did you find most useful in this article? Leave a comment to let us know!

• Hairston, M., & Keene, M. 2003. Successful writing . 5th ed. New York: Norton.
• University of Southern California. 2017. Organizing your social sciences research paper: choosing a title . [Online] Available at: http://libguides.usc.edu/writingguide/title

Thank you so much:) Have a nice day!

Thank you so much, it helped me.. God bless..

Thank you for the excellent article and tips for creating a research work, because I always forget about such an essential element as the keywords when forming topics. In particular, I have found a rapid help with the formation of informative and sound titles that also conforms to the standards and requirements.

I am doing a research work on sales girls or shop girls using qualititative method. Basicly I am from Pakistan and writing on the scenario of mycountry. I am really confused about my research title can you kindly give some suggestions and give me an approperaite tilte

Hi Zubair, Thank you for your question. However, the information you have provided is insufficient for drafting an appropriate title. Information on what exactly you intend to study would be needed in order to draft a meaningful title. Meanwhile, you can try drafting your own title after going through the following articles our website: https://www.enago.com/academy/top-10-tips-on-choosing-an-attractive-research-title/ , https://www.enago.com/academy/writing-a-good-research-title-things-to-avoid/ , https://www.enago.com/academy/write-irresistible-research-paper-title/ We would be happy to give you feedback and suggest changes if required. Did you get a chance to install our free Mobile App? https://www.enago.com/academy/mobile-app/ . Make sure you subscribe to our weekly newsletter https://www.enago.com/academy/subscribe-now/ .

thanks for helping me like this!!

Thank you for this. It helped me improve my research title. I just want to verify to you the title I have just made. “Ensuring the safety: A Quantitative Study of Radio Frequency Identification system among the selected students of ( school’s name ).

(I need your reply asap coz we will be doing the chap. 1 tomorrow. Thank u in advance. 🙂 )

I am actually doing a research paper title. I want to know more further in doing research title. Can you give me some tips on doing a research paper?

Hi Joan, Thank you for your question. We are glad to know that you found our resources useful. Your feedback is very valuable to us. You can try drafting your own title after going through the following articles on our website: https://www.enago.com/academy/top-10-tips-on-choosing-an-attractive-research-title/ , https://www.enago.com/academy/writing-a-good-research-title-things-to-avoid/ , https://www.enago.com/academy/write-irresistible-research-paper-title/

We would be happy to give you feedback and suggest changes if required. Did you get a chance to install our free Mobile App? https://www.enago.com/academy/mobile-app/ . Make sure you subscribe to our weekly newsletter https://www.enago.com/academy/subscribe-now/ .

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Titles in research articles and doctoral dissertations: cross-disciplinary and cross-generic perspectives

• Published: 29 February 2024

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• Jialiang Hao   ORCID: orcid.org/0009-0006-5980-4451 1 , 2  

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Although titles are often regarded as a minimal aspect of academic discourse, they play a crucial role in knowledge construction across various disciplines and genres. This study examined four features of titles, namely, title length, punctuation usage, structure, and content information, with a corpus comprising 1600 titles of research articles (RAs) from top journals and doctoral dissertations (DDs) from prestigious universities across four soft and hard science disciplines. The results confirm disciplinary and generic variations within the titles of these two critical academic genres. Titles in linguistics and medicine are generally longer than those in economics and computer science (CS). Slightly more titles in hard disciplines contain punctuation than do those in soft disciplines. The average title length of RAs is longer than that of DDs, and more RA titles than DD titles have punctuation in all four disciplines, with no apparent difference in the punctuation variety across the two genres, except for CS titles. Nominal group titles and compound titles are the two most common types, and prepositional phrase titles are the least common in all four disciplines and genres. The content information in titles is different in each discipline and genre. These findings are partially congruent with those of previous studies, indicating the significance of further investigating titles across disciplines and genres.

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The researcher thanks the handling editor and the anonymous reviewers for their valuable comments, which significantly contributed to enhancing the quality of the manuscript.

This research was supported and funded by the Scientific Research Program Funded by Shaanxi Provincial Education Department (Program No. 23JK0100).

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500+ Quantitative Research Titles and Topics

Table of Contents

Quantitative research involves collecting and analyzing numerical data to identify patterns, trends, and relationships among variables. This method is widely used in social sciences, psychology , economics , and other fields where researchers aim to understand human behavior and phenomena through statistical analysis. If you are looking for a quantitative research topic, there are numerous areas to explore, from analyzing data on a specific population to studying the effects of a particular intervention or treatment. In this post, we will provide some ideas for quantitative research topics that may inspire you and help you narrow down your interests.

Quantitative Research Titles

Quantitative Research Titles are as follows:

Business and Economics

• “Statistical Analysis of Supply Chain Disruptions on Retail Sales”
• “Quantitative Examination of Consumer Loyalty Programs in the Fast Food Industry”
• “Predicting Stock Market Trends Using Machine Learning Algorithms”
• “Influence of Workplace Environment on Employee Productivity: A Quantitative Study”
• “Impact of Economic Policies on Small Businesses: A Regression Analysis”
• “Customer Satisfaction and Profit Margins: A Quantitative Correlation Study”
• “Analyzing the Role of Marketing in Brand Recognition: A Statistical Overview”
• “Quantitative Effects of Corporate Social Responsibility on Consumer Trust”
• “Price Elasticity of Demand for Luxury Goods: A Case Study”
• “The Relationship Between Fiscal Policy and Inflation Rates: A Time-Series Analysis”
• “Factors Influencing E-commerce Conversion Rates: A Quantitative Exploration”
• “Examining the Correlation Between Interest Rates and Consumer Spending”
• “Standardized Testing and Academic Performance: A Quantitative Evaluation”
• “Teaching Strategies and Student Learning Outcomes in Secondary Schools: A Quantitative Study”
• “The Relationship Between Extracurricular Activities and Academic Success”
• “Influence of Parental Involvement on Children’s Educational Achievements”
• “Digital Literacy in Primary Schools: A Quantitative Assessment”
• “Learning Outcomes in Blended vs. Traditional Classrooms: A Comparative Analysis”
• “Correlation Between Teacher Experience and Student Success Rates”
• “Analyzing the Impact of Classroom Technology on Reading Comprehension”
• “Gender Differences in STEM Fields: A Quantitative Analysis of Enrollment Data”
• “The Relationship Between Homework Load and Academic Burnout”
• “Assessment of Special Education Programs in Public Schools”
• “Role of Peer Tutoring in Improving Academic Performance: A Quantitative Study”

Medicine and Health Sciences

• “The Impact of Sleep Duration on Cardiovascular Health: A Cross-sectional Study”
• “Analyzing the Efficacy of Various Antidepressants: A Meta-Analysis”
• “Patient Satisfaction in Telehealth Services: A Quantitative Assessment”
• “Dietary Habits and Incidence of Heart Disease: A Quantitative Review”
• “Correlations Between Stress Levels and Immune System Functioning”
• “Smoking and Lung Function: A Quantitative Analysis”
• “Influence of Physical Activity on Mental Health in Older Adults”
• “Antibiotic Resistance Patterns in Community Hospitals: A Quantitative Study”
• “The Efficacy of Vaccination Programs in Controlling Disease Spread: A Time-Series Analysis”
• “Role of Social Determinants in Health Outcomes: A Quantitative Exploration”
• “Impact of Hospital Design on Patient Recovery Rates”
• “Quantitative Analysis of Dietary Choices and Obesity Rates in Children”

Social Sciences

• “Examining Social Inequality through Wage Distribution: A Quantitative Study”
• “Impact of Parental Divorce on Child Development: A Longitudinal Study”
• “Social Media and its Effect on Political Polarization: A Quantitative Analysis”
• “The Relationship Between Religion and Social Attitudes: A Statistical Overview”
• “Influence of Socioeconomic Status on Educational Achievement”
• “Quantifying the Effects of Community Programs on Crime Reduction”
• “Public Opinion and Immigration Policies: A Quantitative Exploration”
• “Analyzing the Gender Representation in Political Offices: A Quantitative Study”
• “Impact of Mass Media on Public Opinion: A Regression Analysis”
• “Influence of Urban Design on Social Interactions in Communities”
• “The Role of Social Support in Mental Health Outcomes: A Quantitative Analysis”
• “Examining the Relationship Between Substance Abuse and Employment Status”

Engineering and Technology

• “Performance Evaluation of Different Machine Learning Algorithms in Autonomous Vehicles”
• “Material Science: A Quantitative Analysis of Stress-Strain Properties in Various Alloys”
• “Impacts of Data Center Cooling Solutions on Energy Consumption”
• “Analyzing the Reliability of Renewable Energy Sources in Grid Management”
• “Optimization of 5G Network Performance: A Quantitative Assessment”
• “Quantifying the Effects of Aerodynamics on Fuel Efficiency in Commercial Airplanes”
• “The Relationship Between Software Complexity and Bug Frequency”
• “Machine Learning in Predictive Maintenance: A Quantitative Analysis”
• “Wearable Technologies and their Impact on Healthcare Monitoring”
• “Quantitative Assessment of Cybersecurity Measures in Financial Institutions”
• “Analysis of Noise Pollution from Urban Transportation Systems”
• “The Influence of Architectural Design on Energy Efficiency in Buildings”

Quantitative Research Topics

Quantitative Research Topics are as follows:

• The effects of social media on self-esteem among teenagers.
• A comparative study of academic achievement among students of single-sex and co-educational schools.
• The impact of gender on leadership styles in the workplace.
• The correlation between parental involvement and academic performance of students.
• The effect of mindfulness meditation on stress levels in college students.
• The relationship between employee motivation and job satisfaction.
• The effectiveness of online learning compared to traditional classroom learning.
• The correlation between sleep duration and academic performance among college students.
• The impact of exercise on mental health among adults.
• The relationship between social support and psychological well-being among cancer patients.
• The effect of caffeine consumption on sleep quality.
• A comparative study of the effectiveness of cognitive-behavioral therapy and pharmacotherapy in treating depression.
• The relationship between physical attractiveness and job opportunities.
• The correlation between smartphone addiction and academic performance among high school students.
• The impact of music on memory recall among adults.
• The effectiveness of parental control software in limiting children’s online activity.
• The relationship between social media use and body image dissatisfaction among young adults.
• The correlation between academic achievement and parental involvement among minority students.
• The impact of early childhood education on academic performance in later years.
• The effectiveness of employee training and development programs in improving organizational performance.
• The relationship between socioeconomic status and access to healthcare services.
• The correlation between social support and academic achievement among college students.
• The impact of technology on communication skills among children.
• The effectiveness of mindfulness-based stress reduction programs in reducing symptoms of anxiety and depression.
• The relationship between employee turnover and organizational culture.
• The correlation between job satisfaction and employee engagement.
• The impact of video game violence on aggressive behavior among children.
• The effectiveness of nutritional education in promoting healthy eating habits among adolescents.
• The relationship between bullying and academic performance among middle school students.
• The correlation between teacher expectations and student achievement.
• The impact of gender stereotypes on career choices among high school students.
• The effectiveness of anger management programs in reducing violent behavior.
• The relationship between social support and recovery from substance abuse.
• The correlation between parent-child communication and adolescent drug use.
• The impact of technology on family relationships.
• The effectiveness of smoking cessation programs in promoting long-term abstinence.
• The relationship between personality traits and academic achievement.
• The correlation between stress and job performance among healthcare professionals.
• The impact of online privacy concerns on social media use.
• The effectiveness of cognitive-behavioral therapy in treating anxiety disorders.
• The relationship between teacher feedback and student motivation.
• The correlation between physical activity and academic performance among elementary school students.
• The impact of parental divorce on academic achievement among children.
• The effectiveness of diversity training in improving workplace relationships.
• The relationship between childhood trauma and adult mental health.
• The correlation between parental involvement and substance abuse among adolescents.
• The impact of social media use on romantic relationships among young adults.
• The effectiveness of assertiveness training in improving communication skills.
• The relationship between parental expectations and academic achievement among high school students.
• The correlation between sleep quality and mood among adults.
• The impact of video game addiction on academic performance among college students.
• The effectiveness of group therapy in treating eating disorders.
• The relationship between job stress and job performance among teachers.
• The correlation between mindfulness and emotional regulation.
• The impact of social media use on self-esteem among college students.
• The effectiveness of parent-teacher communication in promoting academic achievement among elementary school students.
• The impact of renewable energy policies on carbon emissions
• The relationship between employee motivation and job performance
• The effectiveness of psychotherapy in treating eating disorders
• The correlation between physical activity and cognitive function in older adults
• The effect of childhood poverty on adult health outcomes
• The impact of urbanization on biodiversity conservation
• The relationship between work-life balance and employee job satisfaction
• The effectiveness of eye movement desensitization and reprocessing (EMDR) in treating trauma
• The correlation between parenting styles and child behavior
• The effect of social media on political polarization
• The impact of foreign aid on economic development
• The relationship between workplace diversity and organizational performance
• The effectiveness of dialectical behavior therapy in treating borderline personality disorder
• The correlation between childhood abuse and adult mental health outcomes
• The effect of sleep deprivation on cognitive function
• The impact of trade policies on international trade and economic growth
• The relationship between employee engagement and organizational commitment
• The effectiveness of cognitive therapy in treating postpartum depression
• The correlation between family meals and child obesity rates
• The effect of parental involvement in sports on child athletic performance
• The impact of social entrepreneurship on sustainable development
• The relationship between emotional labor and job burnout
• The effectiveness of art therapy in treating dementia
• The correlation between social media use and academic procrastination
• The effect of poverty on childhood educational attainment
• The impact of urban green spaces on mental health
• The relationship between job insecurity and employee well-being
• The effectiveness of virtual reality exposure therapy in treating anxiety disorders
• The correlation between childhood trauma and substance abuse
• The effect of screen time on children’s social skills
• The impact of trade unions on employee job satisfaction
• The relationship between cultural intelligence and cross-cultural communication
• The effectiveness of acceptance and commitment therapy in treating chronic pain
• The correlation between childhood obesity and adult health outcomes
• The effect of gender diversity on corporate performance
• The impact of environmental regulations on industry competitiveness.
• The impact of renewable energy policies on greenhouse gas emissions
• The relationship between workplace diversity and team performance
• The effectiveness of group therapy in treating substance abuse
• The correlation between parental involvement and social skills in early childhood
• The effect of technology use on sleep patterns
• The impact of government regulations on small business growth
• The relationship between job satisfaction and employee turnover
• The effectiveness of virtual reality therapy in treating anxiety disorders
• The correlation between parental involvement and academic motivation in adolescents
• The effect of social media on political engagement
• The impact of urbanization on mental health
• The relationship between corporate social responsibility and consumer trust
• The correlation between early childhood education and social-emotional development
• The effect of screen time on cognitive development in young children
• The impact of trade policies on global economic growth
• The relationship between workplace diversity and innovation
• The effectiveness of family therapy in treating eating disorders
• The correlation between parental involvement and college persistence
• The effect of social media on body image and self-esteem
• The impact of environmental regulations on business competitiveness
• The relationship between job autonomy and job satisfaction
• The effectiveness of virtual reality therapy in treating phobias
• The correlation between parental involvement and academic achievement in college
• The effect of social media on sleep quality
• The impact of immigration policies on social integration
• The relationship between workplace diversity and employee well-being
• The effectiveness of psychodynamic therapy in treating personality disorders
• The correlation between early childhood education and executive function skills
• The effect of parental involvement on STEM education outcomes
• The impact of trade policies on domestic employment rates
• The relationship between job insecurity and mental health
• The effectiveness of exposure therapy in treating PTSD
• The correlation between parental involvement and social mobility
• The effect of social media on intergroup relations
• The impact of urbanization on air pollution and respiratory health.
• The relationship between emotional intelligence and leadership effectiveness
• The effectiveness of cognitive-behavioral therapy in treating depression
• The correlation between early childhood education and language development
• The effect of parental involvement on academic achievement in STEM fields
• The impact of trade policies on income inequality
• The relationship between workplace diversity and customer satisfaction
• The effectiveness of mindfulness-based therapy in treating anxiety disorders
• The correlation between parental involvement and civic engagement in adolescents
• The effect of social media on mental health among teenagers
• The impact of public transportation policies on traffic congestion
• The relationship between job stress and job performance
• The effectiveness of group therapy in treating depression
• The correlation between early childhood education and cognitive development
• The effect of parental involvement on academic motivation in college
• The impact of environmental regulations on energy consumption
• The relationship between workplace diversity and employee engagement
• The effectiveness of art therapy in treating PTSD
• The correlation between parental involvement and academic success in vocational education
• The effect of social media on academic achievement in college
• The impact of tax policies on economic growth
• The relationship between job flexibility and work-life balance
• The effectiveness of acceptance and commitment therapy in treating anxiety disorders
• The correlation between early childhood education and social competence
• The effect of parental involvement on career readiness in high school
• The impact of immigration policies on crime rates
• The relationship between workplace diversity and employee retention
• The effectiveness of play therapy in treating trauma
• The correlation between parental involvement and academic success in online learning
• The effect of social media on body dissatisfaction among women
• The impact of urbanization on public health infrastructure
• The relationship between job satisfaction and job performance
• The effectiveness of eye movement desensitization and reprocessing therapy in treating PTSD
• The correlation between early childhood education and social skills in adolescence
• The effect of parental involvement on academic achievement in the arts
• The impact of trade policies on foreign investment
• The relationship between workplace diversity and decision-making
• The effectiveness of exposure and response prevention therapy in treating OCD
• The correlation between parental involvement and academic success in special education
• The impact of zoning laws on affordable housing
• The relationship between job design and employee motivation
• The effectiveness of cognitive rehabilitation therapy in treating traumatic brain injury
• The correlation between early childhood education and social-emotional learning
• The effect of parental involvement on academic achievement in foreign language learning
• The impact of trade policies on the environment
• The relationship between workplace diversity and creativity
• The effectiveness of emotion-focused therapy in treating relationship problems
• The correlation between parental involvement and academic success in music education
• The effect of social media on interpersonal communication skills
• The impact of public health campaigns on health behaviors
• The relationship between job resources and job stress
• The effectiveness of equine therapy in treating substance abuse
• The correlation between early childhood education and self-regulation
• The effect of parental involvement on academic achievement in physical education
• The impact of immigration policies on cultural assimilation
• The relationship between workplace diversity and conflict resolution
• The effectiveness of schema therapy in treating personality disorders
• The correlation between parental involvement and academic success in career and technical education
• The effect of social media on trust in government institutions
• The impact of urbanization on public transportation systems
• The relationship between job demands and job stress
• The correlation between early childhood education and executive functioning
• The effect of parental involvement on academic achievement in computer science
• The effectiveness of cognitive processing therapy in treating PTSD
• The correlation between parental involvement and academic success in homeschooling
• The effect of social media on cyberbullying behavior
• The impact of urbanization on air quality
• The effectiveness of dance therapy in treating anxiety disorders
• The correlation between early childhood education and math achievement
• The effect of parental involvement on academic achievement in health education
• The impact of global warming on agriculture
• The effectiveness of narrative therapy in treating depression
• The correlation between parental involvement and academic success in character education
• The effect of social media on political participation
• The impact of technology on job displacement
• The relationship between job resources and job satisfaction
• The effectiveness of art therapy in treating addiction
• The correlation between early childhood education and reading comprehension
• The effect of parental involvement on academic achievement in environmental education
• The impact of income inequality on social mobility
• The relationship between workplace diversity and organizational culture
• The effectiveness of solution-focused brief therapy in treating anxiety disorders
• The correlation between parental involvement and academic success in physical therapy education
• The effect of social media on misinformation
• The impact of green energy policies on economic growth
• The relationship between job demands and employee well-being
• The correlation between early childhood education and science achievement
• The effect of parental involvement on academic achievement in religious education
• The impact of gender diversity on corporate governance
• The relationship between workplace diversity and ethical decision-making
• The correlation between parental involvement and academic success in dental hygiene education
• The effect of social media on self-esteem among adolescents
• The impact of renewable energy policies on energy security
• The effect of parental involvement on academic achievement in social studies
• The impact of trade policies on job growth
• The relationship between workplace diversity and leadership styles
• The correlation between parental involvement and academic success in online vocational training
• The effect of social media on self-esteem among men
• The impact of urbanization on air pollution levels
• The effectiveness of music therapy in treating depression
• The correlation between early childhood education and math skills
• The effect of parental involvement on academic achievement in language arts
• The impact of immigration policies on labor market outcomes
• The effectiveness of hypnotherapy in treating phobias
• The effect of social media on political engagement among young adults
• The impact of urbanization on access to green spaces
• The relationship between job crafting and job satisfaction
• The effectiveness of exposure therapy in treating specific phobias
• The correlation between early childhood education and spatial reasoning
• The effect of parental involvement on academic achievement in business education
• The impact of trade policies on economic inequality
• The effectiveness of narrative therapy in treating PTSD
• The correlation between parental involvement and academic success in nursing education
• The effect of social media on sleep quality among adolescents
• The impact of urbanization on crime rates
• The relationship between job insecurity and turnover intentions
• The effectiveness of pet therapy in treating anxiety disorders
• The correlation between early childhood education and STEM skills
• The effect of parental involvement on academic achievement in culinary education
• The impact of immigration policies on housing affordability
• The relationship between workplace diversity and employee satisfaction
• The effectiveness of mindfulness-based stress reduction in treating chronic pain
• The correlation between parental involvement and academic success in art education
• The effect of social media on academic procrastination among college students
• The impact of urbanization on public safety services.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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