types of hypothesis in nursing research

• Resources Home 🏠
• Try SciSpace Copilot
• Search research papers
• Add Copilot Extension
• Try AI Detector
• Try Paraphraser
• Try Citation Generator
• April Papers
• June Papers
• July Papers

The Craft of Writing a Strong Hypothesis

Table of Contents

Writing a hypothesis is one of the essential elements of a scientific research paper. It needs to be to the point, clearly communicating what your research is trying to accomplish. A blurry, drawn-out, or complexly-structured hypothesis can confuse your readers. Or worse, the editor and peer reviewers.

A captivating hypothesis is not too intricate. This blog will take you through the process so that, by the end of it, you have a better idea of how to convey your research paper's intent in just one sentence.

What is a Hypothesis?

The first step in your scientific endeavor, a hypothesis, is a strong, concise statement that forms the basis of your research. It is not the same as a thesis statement , which is a brief summary of your research paper .

The sole purpose of a hypothesis is to predict your paper's findings, data, and conclusion. It comes from a place of curiosity and intuition . When you write a hypothesis, you're essentially making an educated guess based on scientific prejudices and evidence, which is further proven or disproven through the scientific method.

The reason for undertaking research is to observe a specific phenomenon. A hypothesis, therefore, lays out what the said phenomenon is. And it does so through two variables, an independent and dependent variable.

The independent variable is the cause behind the observation, while the dependent variable is the effect of the cause. A good example of this is “mixing red and blue forms purple.” In this hypothesis, mixing red and blue is the independent variable as you're combining the two colors at your own will. The formation of purple is the dependent variable as, in this case, it is conditional to the independent variable.

Different Types of Hypotheses‌

Types of hypotheses

Some would stand by the notion that there are only two types of hypotheses: a Null hypothesis and an Alternative hypothesis. While that may have some truth to it, it would be better to fully distinguish the most common forms as these terms come up so often, which might leave you out of context.

Apart from Null and Alternative, there are Complex, Simple, Directional, Non-Directional, Statistical, and Associative and casual hypotheses. They don't necessarily have to be exclusive, as one hypothesis can tick many boxes, but knowing the distinctions between them will make it easier for you to construct your own.

1. Null hypothesis

A null hypothesis proposes no relationship between two variables. Denoted by H 0 , it is a negative statement like “Attending physiotherapy sessions does not affect athletes' on-field performance.” Here, the author claims physiotherapy sessions have no effect on on-field performances. Even if there is, it's only a coincidence.

2. Alternative hypothesis

Considered to be the opposite of a null hypothesis, an alternative hypothesis is donated as H1 or Ha. It explicitly states that the dependent variable affects the independent variable. A good  alternative hypothesis example is “Attending physiotherapy sessions improves athletes' on-field performance.” or “Water evaporates at 100 °C. ” The alternative hypothesis further branches into directional and non-directional.

• Directional hypothesis: A hypothesis that states the result would be either positive or negative is called directional hypothesis. It accompanies H1 with either the ‘<' or ‘>' sign.
• Non-directional hypothesis: A non-directional hypothesis only claims an effect on the dependent variable. It does not clarify whether the result would be positive or negative. The sign for a non-directional hypothesis is ‘≠.'

3. Simple hypothesis

A simple hypothesis is a statement made to reflect the relation between exactly two variables. One independent and one dependent. Consider the example, “Smoking is a prominent cause of lung cancer." The dependent variable, lung cancer, is dependent on the independent variable, smoking.

4. Complex hypothesis

In contrast to a simple hypothesis, a complex hypothesis implies the relationship between multiple independent and dependent variables. For instance, “Individuals who eat more fruits tend to have higher immunity, lesser cholesterol, and high metabolism.” The independent variable is eating more fruits, while the dependent variables are higher immunity, lesser cholesterol, and high metabolism.

5. Associative and casual hypothesis

Associative and casual hypotheses don't exhibit how many variables there will be. They define the relationship between the variables. In an associative hypothesis, changing any one variable, dependent or independent, affects others. In a casual hypothesis, the independent variable directly affects the dependent.

6. Empirical hypothesis

Also referred to as the working hypothesis, an empirical hypothesis claims a theory's validation via experiments and observation. This way, the statement appears justifiable and different from a wild guess.

Say, the hypothesis is “Women who take iron tablets face a lesser risk of anemia than those who take vitamin B12.” This is an example of an empirical hypothesis where the researcher  the statement after assessing a group of women who take iron tablets and charting the findings.

7. Statistical hypothesis

The point of a statistical hypothesis is to test an already existing hypothesis by studying a population sample. Hypothesis like “44% of the Indian population belong in the age group of 22-27.” leverage evidence to prove or disprove a particular statement.

Characteristics of a Good Hypothesis

Writing a hypothesis is essential as it can make or break your research for you. That includes your chances of getting published in a journal. So when you're designing one, keep an eye out for these pointers:

• A research hypothesis has to be simple yet clear to look justifiable enough.
• It has to be testable — your research would be rendered pointless if too far-fetched into reality or limited by technology.
• It has to be precise about the results —what you are trying to do and achieve through it should come out in your hypothesis.
• A research hypothesis should be self-explanatory, leaving no doubt in the reader's mind.
• If you are developing a relational hypothesis, you need to include the variables and establish an appropriate relationship among them.
• A hypothesis must keep and reflect the scope for further investigations and experiments.

Separating a Hypothesis from a Prediction

Outside of academia, hypothesis and prediction are often used interchangeably. In research writing, this is not only confusing but also incorrect. And although a hypothesis and prediction are guesses at their core, there are many differences between them.

A hypothesis is an educated guess or even a testable prediction validated through research. It aims to analyze the gathered evidence and facts to define a relationship between variables and put forth a logical explanation behind the nature of events.

Predictions are assumptions or expected outcomes made without any backing evidence. They are more fictionally inclined regardless of where they originate from.

For this reason, a hypothesis holds much more weight than a prediction. It sticks to the scientific method rather than pure guesswork. "Planets revolve around the Sun." is an example of a hypothesis as it is previous knowledge and observed trends. Additionally, we can test it through the scientific method.

Whereas "COVID-19 will be eradicated by 2030." is a prediction. Even though it results from past trends, we can't prove or disprove it. So, the only way this gets validated is to wait and watch if COVID-19 cases end by 2030.

Finally, How to Write a Hypothesis

Quick tips on writing a hypothesis

1.  Be clear about your research question

A hypothesis should instantly address the research question or the problem statement. To do so, you need to ask a question. Understand the constraints of your undertaken research topic and then formulate a simple and topic-centric problem. Only after that can you develop a hypothesis and further test for evidence.

2. Carry out a recce

Once you have your research's foundation laid out, it would be best to conduct preliminary research. Go through previous theories, academic papers, data, and experiments before you start curating your research hypothesis. It will give you an idea of your hypothesis's viability or originality.

Making use of references from relevant research papers helps draft a good research hypothesis. SciSpace Discover offers a repository of over 270 million research papers to browse through and gain a deeper understanding of related studies on a particular topic. Additionally, you can use SciSpace Copilot , your AI research assistant, for reading any lengthy research paper and getting a more summarized context of it. A hypothesis can be formed after evaluating many such summarized research papers. Copilot also offers explanations for theories and equations, explains paper in simplified version, allows you to highlight any text in the paper or clip math equations and tables and provides a deeper, clear understanding of what is being said. This can improve the hypothesis by helping you identify potential research gaps.

3. Create a 3-dimensional hypothesis

Variables are an essential part of any reasonable hypothesis. So, identify your independent and dependent variable(s) and form a correlation between them. The ideal way to do this is to write the hypothetical assumption in the ‘if-then' form. If you use this form, make sure that you state the predefined relationship between the variables.

In another way, you can choose to present your hypothesis as a comparison between two variables. Here, you must specify the difference you expect to observe in the results.

4. Write the first draft

Now that everything is in place, it's time to write your hypothesis. For starters, create the first draft. In this version, write what you expect to find from your research.

Clearly separate your independent and dependent variables and the link between them. Don't fixate on syntax at this stage. The goal is to ensure your hypothesis addresses the issue.

5. Proof your hypothesis

After preparing the first draft of your hypothesis, you need to inspect it thoroughly. It should tick all the boxes, like being concise, straightforward, relevant, and accurate. Your final hypothesis has to be well-structured as well.

Research projects are an exciting and crucial part of being a scholar. And once you have your research question, you need a great hypothesis to begin conducting research. Thus, knowing how to write a hypothesis is very important.

Now that you have a firmer grasp on what a good hypothesis constitutes, the different kinds there are, and what process to follow, you will find it much easier to write your hypothesis, which ultimately helps your research.

Now it's easier than ever to streamline your research workflow with SciSpace Discover . Its integrated, comprehensive end-to-end platform for research allows scholars to easily discover, write and publish their research and fosters collaboration.

It includes everything you need, including a repository of over 270 million research papers across disciplines, SEO-optimized summaries and public profiles to show your expertise and experience.

If you found these tips on writing a research hypothesis useful, head over to our blog on Statistical Hypothesis Testing to learn about the top researchers, papers, and institutions in this domain.

Frequently Asked Questions (FAQs)

1. what is the definition of hypothesis.

According to the Oxford dictionary, a hypothesis is defined as “An idea or explanation of something that is based on a few known facts, but that has not yet been proved to be true or correct”.

2. What is an example of hypothesis?

The hypothesis is a statement that proposes a relationship between two or more variables. An example: "If we increase the number of new users who join our platform by 25%, then we will see an increase in revenue."

3. What is an example of null hypothesis?

A null hypothesis is a statement that there is no relationship between two variables. The null hypothesis is written as H0. The null hypothesis states that there is no effect. For example, if you're studying whether or not a particular type of exercise increases strength, your null hypothesis will be "there is no difference in strength between people who exercise and people who don't."

4. What are the types of research?

• Fundamental research

• Applied research

• Qualitative research

• Quantitative research

• Mixed research

• Exploratory research

• Longitudinal research

• Cross-sectional research

• Field research

• Laboratory research

• Fixed research

• Flexible research

• Action research

• Policy research

• Classification research

• Comparative research

• Causal research

• Inductive research

• Deductive research

5. How to write a hypothesis?

• Your hypothesis should be able to predict the relationship and outcome.

• Avoid wordiness by keeping it simple and brief.

• Your hypothesis should contain observable and testable outcomes.

• Your hypothesis should be relevant to the research question.

6. What are the 2 types of hypothesis?

• Null hypotheses are used to test the claim that "there is no difference between two groups of data".

• Alternative hypotheses test the claim that "there is a difference between two data groups".

7. Difference between research question and research hypothesis?

A research question is a broad, open-ended question you will try to answer through your research. A hypothesis is a statement based on prior research or theory that you expect to be true due to your study. Example - Research question: What are the factors that influence the adoption of the new technology? Research hypothesis: There is a positive relationship between age, education and income level with the adoption of the new technology.

8. What is plural for hypothesis?

The plural of hypothesis is hypotheses. Here's an example of how it would be used in a statement, "Numerous well-considered hypotheses are presented in this part, and they are supported by tables and figures that are well-illustrated."

9. What is the red queen hypothesis?

The red queen hypothesis in evolutionary biology states that species must constantly evolve to avoid extinction because if they don't, they will be outcompeted by other species that are evolving. Leigh Van Valen first proposed it in 1973; since then, it has been tested and substantiated many times.

10. Who is known as the father of null hypothesis?

The father of the null hypothesis is Sir Ronald Fisher. He published a paper in 1925 that introduced the concept of null hypothesis testing, and he was also the first to use the term itself.

11. When to reject null hypothesis?

You need to find a significant difference between your two populations to reject the null hypothesis. You can determine that by running statistical tests such as an independent sample t-test or a dependent sample t-test. You should reject the null hypothesis if the p-value is less than 0.05.

You might also like

Consensus GPT vs. SciSpace GPT: Choose the Best GPT for Research

Literature Review and Theoretical Framework: Understanding the Differences

Types of Essays in Academic Writing - Quick Guide (2024)

The First Step: Ask; Fundamentals of Evidence-Based Nursing Practice

In this module, we will learn about identifying the problem, start the “Ask” process with developing an answerable clinical question, and learn about purpose statements and hypotheses.

Content includes:

• Identifying the problem
• Determining the Population, Intervention, Comparison, and Outcome (PICO)
• Asking a Research/Clinical Question (Based on PICO)

Statements of Purpose

Objectives:

• Describe the process of developing a research/practice problem.
• Describe the components of a PICO.
• Identify different types of PICOs.
• Distinguish function and form of statements of purpose.
• Describe the function and characteristics of hypotheses.

Development of a Research/Practice Problem

Practice questions frequently arise from day-to-day problems that are encountered by providers (Dearholt & Dang, 2012). Often, these problems are very obvious. However, sometimes we need to back up and take a close look at the status quo to see underlying issues. The basis for any research project is indeed the underlying problem or issue. A good problem statement or paragraph is a declaration of what it is that is problematic or what it is that we do not know much about (a gap in knowledge) (Polit & Beck, 2018).

The process of defining the practice/clinical problem begins by seeking answers to clinical concerns. This is the first step in the EBP process: To ask . We start by asking some broad questions to help guide the process of developing our practice problem.

• Is there evidence that the current treatment works?
• Does the current practice help the patient?
• Why are we doing the current practice?
• Should we be doing the current practice this way?
• Is there a way to do this current practice more efficiently?
• Is there a more cost-effective method to do this practice?

Problem Statements:

For our EBP Project, we will need to ask these broad questions and then develop our problem that exists. This establishes the “background” of the issue we want to know more about.

For example, if we are choosing a clinical question based on wanting to know if adjunct music therapy helps decrease postoperative pain levels than just pharmaceuticals alone, we might consider the underlying problems of:

• Postoperative pain is not adequately managed in greater than 80% of patients in the US, although rates vary depending on such factors as type of surgery performed, analgesic/anesthetic intervention used, and time elapsed after surgery (Gan, 2017).
• Poorly controlled acute postoperative pain is associated with increased morbidity, functional and quality-of-life impairment, delayed recovery time, prolonged duration of opioid use, and higher health-care costs (Gan, 2017).
• Multimodal analgesic techniques are widely used but new evidence is disappointing (Rawal, 2016).

In the above examples, we are establishing that poorly managed postoperative pain is a problem. Thus, looking at evidence about adjunctive music therapy may help to address how we might manage pain more effectively. These are our problem statements. This would be our introduction section on the EBP poster. For the sake of our EBP poster, you do not need to list these on the poster references. A heads up: The sources used to help develop our research/clinical program should not be the same resources that we use to answer our upcoming clinical question. In essence, we will be conducting two literature reviews: One, to establish the underlying problem; and, two: To find published research that helps to answer our developed clinical question.

Here is the introduction to the article titled, “The relationships among pain, depression, and physical activity in patients with heart failure” (Haedtke et al, 2017). You can read that the underlying problem is multifocal: 67% of patient with heart failure (HF) experience pain, depression is a comorbidity that affects 22% to 42% of HF patients, and that little attention has been paid to this relationship in patients with HF. The researchers have established the need for further research and why further research is needed.

Here is another example of how the clinical problem is addressed in an EBP poster that wants to appraise existing evidence related to dressing choice for decubitus ulcers.

When trying to communicate clinical problems, there are two main sources (Titler et al, 1994, 2001):

• Problem-focused triggers : These are identified by staff during routine monitoring of quality, risk, adverse events, financial, or benchmarking data.
• Knowledge-focused triggers : There are identified through reading published evidence or learning new information at conferences or other professional meetings.

Sources of Evidence-Based Clinical Problems:

Most problem statements have the following components:

• Problem identification: What is wrong with the current situation or action?
• Background: What is the nature of the problem or the context of the situation? (this helps to establish the why)
• Scope of the problem: How many people are affected? Is this a small problem? Big problem? Potential to grow quickly to a large problem? Has been increasing/decreasing recently?
• Consequences of the problem: If we do nothing or leave as the status quo, what is the cost of not  fixing the issue?
• Knowledge gaps: What information about the problem is lacking? We need to know what we do not know.
• Proposed solution: How will the information or evidence contribute to the solution of the problem?

If you are stumped on a topic, ask faculty, RNs at local facilities, colleagues, and key stakeholders at local facilities for some ideas! There is usually “something” that the nursing field is concerned about or has questions about.

Components of a PICO Question

After we have asked ourselves some background questions, we need to develop a foreground (focused) question. A thoughtful development of a well-structured foreground clinical/practice question is important because the question drives the strategies that you will use to search for the published evidence. The question needs to be very specific, non-ambiguous , and measurable in order to find the relevant evidence needed and also increased the likelihood that you will find what you are looking for.

In developing your clinical/practice question, there is a helpful format to utilize to establish the key component. This format includes the Patient/Population, Intervention/Influence/Exposure, Comparison, and Outcome (PICO) (Richardson, Wilson, Nishikawa, & Hayward, 1995).

Let’s dive into each component to better understand.

P atient, population, or problem: We want to describe the patient, the population, or the problem. Get specific. We will want to know exactly who we are wanting to know about. Consider age, gender, setting of the patient (e.g. postoperative), and/or symptoms.

I ntervention: The intervention is the action or, in other words, the treatment, process of care, education given, or assessment approaches. We will come back to this in more depth, but for now remember that the intervention is also called the “Independent Variable”.

C omparison: Here we are comparing with other interventions. A comparison can be standard of care that already exists, current practice, an opposite intervention/action, or a different intervention/action.

O utcome: What is that that we are looking at for a result or consequence of the intervention? The outcome needs to have a metric for actually measuring results. The outcome can include quality of life, patient satisfaction, cost impacts, or treatment results. The outcome is also called the “Dependent Variable”.

The PICO question is a critical aspect of the EBP project to guide the problem identification and create components that can be used to shape the literature search.  

Let’s watch a nice YouTube video, “PICO: A Model for Evidence-Based Research”:

“PICO: A Model for Evidence Based Research” by Binghamton University Libraries. Licensed CCY BY .

Great! Okay, let’s move on and discuss the various types of PICOs.

Types of PICOs

Before we start developing our clinical question, let’s go over the various types of PICOs and the clinical question that can result from the components. There are various types of PICOs but we are concerned with the therapy/treatment/intervention format of PICO for our EBP posters. 

Let’s take a look at the various types of PICOs:

The first step in developing a research or clinical practice question is developing your PICO. Well, we’ve done that above. You will select each component of your PICO and then turn that into your question. Making the EBP question as specific as possible really helps to identify specific terms and narrow the search, which will result in reducing the time it times searching for relevant evidence.

Once you have your pertinent clinical question, you will use the components to begin your search in published literature for articles that help to answer your question. In class, we will practice with various situations to develop PICOs and clinical questions.

Many articles have the researcher’s statement of purpose (sometimes referred to as “aim”, “goal”, or “objective”) for their research project. This helps to identify what the overarching direction of inquiry may be. You do not need a statement of purpose/aim/goal/objective for your EBP poster. However, knowing what a statement of purpose is will help you when appraising articles to help answer your clinical question.

The following statement of purpose was written as an aim. The population (P) was identified as patients with HF, the interventions (I) included physical activity/exercise, and the outcomes (O) included pain, depression, total activity time, and sitting time as correlated with the interventions.

In the articles above, the authors made it easy and included their statements of purpose within the abstract at the beginning of the article. Most articles do not feature this ease, and you will need to read the introduction or methodology section of the article to find the statement of purpose, much like within article 3.1.

In qualitative studies, the statement of purpose usually indicates the nature of the inquiry, the key concept, the key phenomenon, and the population.

Function and Characteristics of Hypotheses.

A hypothesis (plural: hypothes es ) is a statement of predicted outcome. Meaning, it is an educated and formulated guess as to how the intervention (independent variable – more on that soon!) impacts the outcome (dependent variable). It is not always a cause and effect. Sometimes there can be just a simple association or correlation. We will come back to that in a few modules.

In your PICO statement, you can think of the “I” as the independent variable and the “O” as the dependent variable . Variables will begin making more sense as we go. But for now, remember this:

Independent Variable (IV): This is a measure that can be manipulated by the researcher. Perhaps it is a medication, an educational program, or a survey. The independent variable enacts change (or not) onto the independent variable. 

Dependent Variable  (DV): This is the result of the independent variable. This is the variable that we utilize statistical analyses to measure. For instance, if we are intervening with a blood pressure medication (our IV), then our DV would be the measurement of the actual blood pressure.

Most of the time, a hypothesis results from a well-worded research question. Here is an example:

Research Question : “Does sexual abuse in childhood affect the development of irritable bowel syndrome in women?”

Research Hypothesis : Women (P) who were sexually abused in childhood (I) have a higher incidence of irritable bowel syndrome (O) than women who were not abused (C).

You may note in that hypothesis that there is a predicted direction of outcome. One thing leads to something.

But, why do we need a hypothesis? First, they help to promote critical thinking. Second, it gives the researcher a way to measure a relationship. Suppose we conducted a study guided only by a research question. Take the above question, for example. Without a hypothesis, the researcher is seemingly prepared to accept any  result (Polit & Beck, 2021). The problem with that is that it is almost always possible to explain something superficially after the fact, even if the findings are inconclusive. A hypothesis reduces the possibility that spurious results will be misconstrued (Polit & Beck, 2021).

Not all research articles will list a hypothesis. This makes it more difficult to critically appraise the results. That is not to say that the results would be invalidated, but it should ignite a spirit of further inquiry as to if the results are valid.

Hypotheses (also called alternative hypothesis) can be stated as:

• Directional or nondirectional
• Simple or complex
• Research or Null

Simple hypothesis : Statement of causal (cause and effect) relationship – one independent variable (intervention) and one dependent variable (outcome).

Example : If you stay up late, then you feel tired the next day.

Complex hypothesis : Statement of causal (cause and effect) or associative (not causal) between two or more independent variables (interventions) and/or two or more dependent variables (outcomes).

Example :  Higher the poverty, higher the illiteracy in society, higher will be the rate of crime (three variables – two independent variables and one dependent variable).

Directional hypothesis : Specifies not only the existence but also the expected direction of the relationship between the dependent (outcome) and the independent (intervention) variables. You will also see this called “One-tailed hypothesis”.

Example : Depression scores will decrease  following a 6-week intervention.

Nondirectional hypothesis : Does not specify the direction of relationship between the variables. You will also see this called “Two-tailed hypothesis”.

Example : College students will perform differently from elementary school students on a memory task (without predicting which group of students will perform better). 

Null hypothesis : The null hypothesis assumes that any kind of difference between the chosen characteristics that you see in a set of data is due to chance. Now, the null hypothesis is why the plain old hypothesis is also called alternative hypothesis. We don’t just assume that the hypothesis is true. So, it is considered an alternative to something just happening by chance (null).

Example : Let’s say our research question is, “Do teens use cell phones to access the internet more than adults?” – our null hypothesis could state: Age has no effect on how cell phones are used for internet access.

And then, further develop the problem and background through finding existing literature to help answer the following questions:

• Knowledge gaps: What information about the problem is lacking? We need to know what we do not  know.

With the previous example of pain in the pediatric population, here is an example of an Introduction section from a past student poster:

• What was the research problem? Was the problem statement easy to locate and was it clearly stated? Did the problem statement build a coherent and persuasive argument for the new study?
• Does the problem have significance for nursing?
• Was there a good fit between the research problem and the paradigm (and tradition) within which the research was conducted?
• Did the report formally present a statement of purpose, research question, and/or hypotheses? Was this information communicated clearly and concisely, and was it placed in a logical and useful location?
• Were purpose statements or research questions worded appropriately (e.g., were key concepts/variables identified and the population specified?
• If there were no formal hypotheses, was their absence justified? Were statistical tests used in analyzing the data despite the absence of stated hypotheses?
• Were hypotheses (if any) properly worded—did they state a predicted relationship between two or more variables? Were they presented as research or as null hypotheses?

References & Attribution

“ Green check mark ” by rawpixel licensed CC0 .

“ Light bulb doodle ” by rawpixel licensed CC0 .

“ Magnifying glass ” by rawpixel licensed CC0

“ Orange flame ” by rawpixel licensed CC0 .

Chen, P., Nunez-Smith, M., Bernheim, S… (2010). Professional experiences of international medical graduates practicing primary care in the United States. Journal of General Internal Medicine, 25 (9), 947-53.

Dearholt, S.L., & Dang, D. (2012). Johns Hopkins nursing evidence-based practice: Model and guidelines (2nd Ed.). Indianapolis, IN: Sigma Theta Tau International. 

Gan, T. (2017). Poorly controlled postoperative pain: Prevalence, consequences, and prevention. Journal of Pain Research, 10, 2287-2298.

Genc, A., Can, G., Aydiner, A. (2012). The efficiency of the acupressure in prevention of the chemotherapy-induced nausea and vomiting. Support Care Cancer, 21 , 253-261.

Haedtke, C., Smith, M., VanBuren, J., Kein, D., Turvey, C. (2017). The relationships among pain, depression, and physical activity in patients with heart failure. Journal of Cardiovascular Nursing, 32 (5), E21-E25.

Pankong, O., Pothiban, L., Sucamvang, K., Khampolsiri, T. (2018). A randomized controlled trial of enhancing positive aspects of caregiving in Thai dementia caregivers for dementia. Pacific Rim Internal Journal of Nursing Res, 22 (2), 131-143.

Polit, D. & Beck, C. (2021).  Lippincott CoursePoint Enhanced for Polit’s Essentials of Nursing Research  (10th ed.). Wolters Kluwer Health.

Rawal, N. (2016). Current issues in postoperative pain management. European Journal of Anaesthesiology, 33 , 160-171.

Richardson, W.W., Wilson, M.C., Nishikawa, J., & Hayward, R.S. (1995). The well-built clinical question: A key to evidence-based decisions. American College of Physicians, 123 (3), A12-A13.

Titler, M. G., Kleiber, C., Steelman, V.J. Rakel, B. A. Budreau, G., Everett,…Goode, C.J. (2001). The Iowa model of evidence-based practice to promote quality care. Critical Care Nursing Clinics of North America, 13 (4), 497-509.

Evidence-Based Practice & Research Methodologies Copyright © by Tracy Fawns is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Share This Book

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base

Methodology

• How to Write a Strong Hypothesis | Steps & Examples

How to Write a Strong Hypothesis | Steps & Examples

Published on May 6, 2022 by Shona McCombes . Revised on November 20, 2023.

A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection .

Example: Hypothesis

Daily apple consumption leads to fewer doctor’s visits.

Table of contents

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, other interesting articles, frequently asked questions about writing hypotheses.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Variables in hypotheses

Hypotheses propose a relationship between two or more types of variables .

• An independent variable is something the researcher changes or controls.
• A dependent variable is something the researcher observes and measures.

If there are any control variables , extraneous variables , or confounding variables , be sure to jot those down as you go to minimize the chances that research bias  will affect your results.

In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .

Receive feedback on language, structure, and formatting

Professional editors proofread and edit your paper by focusing on:

• Academic style
• Vague sentences
• Style consistency

See an example

Step 1. Ask a question

Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.

Step 2. Do some preliminary research

Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.

At this stage, you might construct a conceptual framework to ensure that you’re embarking on a relevant topic . This can also help you identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalize more complex constructs.

Step 3. Formulate your hypothesis

Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.

4. Refine your hypothesis

You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:

• The relevant variables
• The specific group being studied
• The predicted outcome of the experiment or analysis

5. Phrase your hypothesis in three ways

To identify the variables, you can write a simple prediction in  if…then form. The first part of the sentence states the independent variable and the second part states the dependent variable.

In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.

If you are comparing two groups, the hypothesis can state what difference you expect to find between them.

6. Write a null hypothesis

If your research involves statistical hypothesis testing , you will also have to write a null hypothesis . The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .

• H 0 : The number of lectures attended by first-year students has no effect on their final exam scores.
• H 1 : The number of lectures attended by first-year students has a positive effect on their final exam scores.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

Here's why students love Scribbr's proofreading services

Discover proofreading & editing

A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

Cite this Scribbr article

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

McCombes, S. (2023, November 20). How to Write a Strong Hypothesis | Steps & Examples. Scribbr. Retrieved April 17, 2024, from https://www.scribbr.com/methodology/hypothesis/

Is this article helpful?

Shona McCombes

Other students also liked, construct validity | definition, types, & examples, what is a conceptual framework | tips & examples, operationalization | a guide with examples, pros & cons, unlimited academic ai-proofreading.

✔ Document error-free in 5minutes ✔ Unlimited document corrections ✔ Specialized in correcting academic texts

An official website of the United States government

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

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

• Publications
• Account settings
• Browse Titles

NCBI Bookshelf. A service of the National Library of Medicine, National Institutes of Health.

Institute of Medicine (US) Division of Health Care Services. Nursing and Nursing Education: Public Policies and Private Actions. Washington (DC): National Academies Press (US); 1983.

Nursing and Nursing Education: Public Policies and Private Actions.

• Hardcopy Version at National Academies Press

Appendix 8 Nursing Research: Definitions and Directions

In order to provide further insight into the need for, philosophy, and scope of nursing research this appendix presents a position statement issued by the Commission on Nursing Research of the American Nurses' Association. It is quoted here in its entirety: 1

Recent years have seen a growing awareness among the public that valuable resources are finite and their use must be carefully considered. In this context, increasing attention is being given to the relative cost of various strategies for utilizing health care resources to meet the present and emerging needs of the nation. Concurrently, nurses are assuming increased decision-making responsibility for the delivery of health care, and they can be expected to continue to assume greater responsibility in the future. Therefore, the timeliness and desirability of identifying directions for nursing research that should receive priority in funding and effort in the 1980s is apparent.

The priorities identified below were developed by the Commission on Nursing Research of the American Nurses' Association, a nine-member group of nurses actively engaged in research whose backgrounds represent considerable diversity in preparation and experience. The priorities represent the consensus of the commissioners, developed through a process of thoughtful discussion and careful deliberation with colleagues.

Accountability to the public for the humane use of knowledge in providing effective and high quality services is the hallmark of a profession. Thus, the preeminent goal of scientific inquiry by nurses is the ongoing development of knowledge for use in the practice of nursing; priorities are stated in that context. Other guiding considerations were the present and anticipated health problems of the population; a historic appreciation of the circumstances in which nursing action has been most beneficial; nursing's philosophical orientation, in which emphasis is on a synthesis of psychosocial and biomedical phenomena to the end of promoting health and effective functioning; and projections regarding the types of decisions nurses will be making in the last decades of the twentieth century. New, unanticipated problems will undoubtedly confront the health care resources of the country; yet it is clear that many of the problems of the future are already manifest today. New knowledge is essential to bring about effective solutions. Nursing research directed to clinical needs can contribute in a significant way to development of those solutions.

• Definition of Nursing Research

Nursing research develops knowledge about health and the promotion of health over the full lifespan, care of persons with health problems and disabilities, and nursing actions to enhance the ability of individuals to respond effectively to actual or potential health problems.

These foci of nursing research complement those of biomedical research, which is primarily concerned with causes and treatments of disease. Advancements in biomedical research have resulted in increased life expectancies, including life expectancies of those with serious injury and those with chronic or terminal disease. These biomedical advances have thus led to growth in the numbers of those who require nursing care to live with health problems, such as the frail elderly, the chronically ill, and the terminally ill.

Research conducted by nurses includes various types of studies in order to derive clinical interventions to assist those who require nursing care. The complexity of nursing research and its broad scope often require scientific underpinning from several disciplines. Hence, nursing research cuts across traditional research lines, and draws its methods from several fields.

• Directions for Research

Priority should be given to nursing research that would generate knowledge to guide practice in:

Promoting health, well-being, and competency for personal care among all age groups;

Preventing health problems throughout the life span that have the potential to reduce productivity and satisfaction;

Decreasing the negative impact of health problems on coping abilities, productivity, and life satisfaction of individuals and families;

Ensuring that the care needs of particularly vulnerable groups are met through appropriate strategies;

Designing and developing health care systems that are cost-effective in meeting the nursing needs of the population.

Examples of research consistent with these priorities include the following:

• Identification of determinants (personal and environmental, including social support networks) of wellness and health functioning in individuals and families, e.g. avoidance of abusive behaviors such as alcoholism and drug use, successful adaptation to chronic illness, and coping with the last days of life.
• Identification of phenomena that negatively influence the course of recovery and that may be alleviated by nursing practice, such as, for example, anorexia, diarrhea, sleep deprivation, deficiencies in nutrients, electrolyte imbalances, and infections.
• Development and testing of care strategies to do the following: Facilitate individuals' ability to adopt and maintain health enhancing behaviors (e.g. alterations in diet and exercise). Enhance patients' ability to manage acute and chronic illness in such a way as to minimize or eliminate the necessity of institutionalization and to maximize well-being. Reduce stressful responses associated with the medical management of patients (e.g. surgical procedures, intrusive examination procedures, or use of extensive monitoring devices). Provide more effective care to high-risk populations (e.g. maternal and child care service to vulnerable mothers and infants, family planning services to young teenagers, services designed to enhance self-care in the chronically ill and the very old). Enhance the care of clients culturally different from the majority (e.g. Black Americans, Mexican-Americans, Native Americans) and clients with special problems (e.g. teenagers, prisoners, and the mentally ill), and the underserved (the elderly, the poor, and the rural).
• Design and assessment, in terms of effectiveness and cost, of models for delivering nursing care strategies found to be effective in clinical studies.

All of the foregoing are directly related to the priority of developing the knowledge and information needed for improvement of the practice of nursing.

While priority should be given to this form of clinical research, there is no intent to discourage other forms of nursing research. These would include such investigations as those utilizing historical and philosophical modes of inquiry, and studies of manpower for nursing education, practice, and research, as well as studies of quality assurance for nursing and those for establishment of criterion measures for practice and education.

American Nurses' Association. Research priorities for the 1980s: Generating a scientific basis for nursing practice (Publication No. D-68). Kansas City, Mo.: American Nurses' Association, 1981.

• Cite this Page Institute of Medicine (US) Division of Health Care Services. Nursing and Nursing Education: Public Policies and Private Actions. Washington (DC): National Academies Press (US); 1983. Appendix 8, Nursing Research: Definitions and Directions.
• PDF version of this title (2.7M)

In this Page

Recent activity.

• Nursing Research: Definitions and Directions - Nursing and Nursing Education Nursing Research: Definitions and Directions - Nursing and Nursing Education

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

Connect with NLM

National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894

Web Policies FOIA HHS Vulnerability Disclosure

Help Accessibility Careers

Research Hypothesis In Psychology: Types, & Examples

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

A research hypothesis, in its plural form “hypotheses,” is a specific, testable prediction about the anticipated results of a study, established at its outset. It is a key component of the scientific method .

Hypotheses connect theory to data and guide the research process towards expanding scientific understanding

Some key points about hypotheses:

• A hypothesis expresses an expected pattern or relationship. It connects the variables under investigation.
• It is stated in clear, precise terms before any data collection or analysis occurs. This makes the hypothesis testable.
• A hypothesis must be falsifiable. It should be possible, even if unlikely in practice, to collect data that disconfirms rather than supports the hypothesis.
• Hypotheses guide research. Scientists design studies to explicitly evaluate hypotheses about how nature works.
• For a hypothesis to be valid, it must be testable against empirical evidence. The evidence can then confirm or disprove the testable predictions.
• Hypotheses are informed by background knowledge and observation, but go beyond what is already known to propose an explanation of how or why something occurs.

Predictions typically arise from a thorough knowledge of the research literature, curiosity about real-world problems or implications, and integrating this to advance theory. They build on existing literature while providing new insight.

Types of Research Hypotheses

Alternative hypothesis.

The research hypothesis is often called the alternative or experimental hypothesis in experimental research.

It typically suggests a potential relationship between two key variables: the independent variable, which the researcher manipulates, and the dependent variable, which is measured based on those changes.

The alternative hypothesis states a relationship exists between the two variables being studied (one variable affects the other).

A hypothesis is a testable statement or prediction about the relationship between two or more variables. It is a key component of the scientific method. Some key points about hypotheses:

• Important hypotheses lead to predictions that can be tested empirically. The evidence can then confirm or disprove the testable predictions.

In summary, a hypothesis is a precise, testable statement of what researchers expect to happen in a study and why. Hypotheses connect theory to data and guide the research process towards expanding scientific understanding.

An experimental hypothesis predicts what change(s) will occur in the dependent variable when the independent variable is manipulated.

It states that the results are not due to chance and are significant in supporting the theory being investigated.

The alternative hypothesis can be directional, indicating a specific direction of the effect, or non-directional, suggesting a difference without specifying its nature. It’s what researchers aim to support or demonstrate through their study.

Null Hypothesis

The null hypothesis states no relationship exists between the two variables being studied (one variable does not affect the other). There will be no changes in the dependent variable due to manipulating the independent variable.

It states results are due to chance and are not significant in supporting the idea being investigated.

The null hypothesis, positing no effect or relationship, is a foundational contrast to the research hypothesis in scientific inquiry. It establishes a baseline for statistical testing, promoting objectivity by initiating research from a neutral stance.

Many statistical methods are tailored to test the null hypothesis, determining the likelihood of observed results if no true effect exists.

This dual-hypothesis approach provides clarity, ensuring that research intentions are explicit, and fosters consistency across scientific studies, enhancing the standardization and interpretability of research outcomes.

Nondirectional Hypothesis

A non-directional hypothesis, also known as a two-tailed hypothesis, predicts that there is a difference or relationship between two variables but does not specify the direction of this relationship.

It merely indicates that a change or effect will occur without predicting which group will have higher or lower values.

For example, “There is a difference in performance between Group A and Group B” is a non-directional hypothesis.

Directional Hypothesis

A directional (one-tailed) hypothesis predicts the nature of the effect of the independent variable on the dependent variable. It predicts in which direction the change will take place. (i.e., greater, smaller, less, more)

It specifies whether one variable is greater, lesser, or different from another, rather than just indicating that there’s a difference without specifying its nature.

For example, “Exercise increases weight loss” is a directional hypothesis.

Falsifiability

The Falsification Principle, proposed by Karl Popper , is a way of demarcating science from non-science. It suggests that for a theory or hypothesis to be considered scientific, it must be testable and irrefutable.

Falsifiability emphasizes that scientific claims shouldn’t just be confirmable but should also have the potential to be proven wrong.

It means that there should exist some potential evidence or experiment that could prove the proposition false.

However many confirming instances exist for a theory, it only takes one counter observation to falsify it. For example, the hypothesis that “all swans are white,” can be falsified by observing a black swan.

For Popper, science should attempt to disprove a theory rather than attempt to continually provide evidence to support a research hypothesis.

Can a Hypothesis be Proven?

Hypotheses make probabilistic predictions. They state the expected outcome if a particular relationship exists. However, a study result supporting a hypothesis does not definitively prove it is true.

All studies have limitations. There may be unknown confounding factors or issues that limit the certainty of conclusions. Additional studies may yield different results.

In science, hypotheses can realistically only be supported with some degree of confidence, not proven. The process of science is to incrementally accumulate evidence for and against hypothesized relationships in an ongoing pursuit of better models and explanations that best fit the empirical data. But hypotheses remain open to revision and rejection if that is where the evidence leads.

• Disproving a hypothesis is definitive. Solid disconfirmatory evidence will falsify a hypothesis and require altering or discarding it based on the evidence.
• However, confirming evidence is always open to revision. Other explanations may account for the same results, and additional or contradictory evidence may emerge over time.

We can never 100% prove the alternative hypothesis. Instead, we see if we can disprove, or reject the null hypothesis.

If we reject the null hypothesis, this doesn’t mean that our alternative hypothesis is correct but does support the alternative/experimental hypothesis.

Upon analysis of the results, an alternative hypothesis can be rejected or supported, but it can never be proven to be correct. We must avoid any reference to results proving a theory as this implies 100% certainty, and there is always a chance that evidence may exist which could refute a theory.

How to Write a Hypothesis

• Identify variables . The researcher manipulates the independent variable and the dependent variable is the measured outcome.
• Operationalized the variables being investigated . Operationalization of a hypothesis refers to the process of making the variables physically measurable or testable, e.g. if you are about to study aggression, you might count the number of punches given by participants.
• Decide on a direction for your prediction . If there is evidence in the literature to support a specific effect of the independent variable on the dependent variable, write a directional (one-tailed) hypothesis. If there are limited or ambiguous findings in the literature regarding the effect of the independent variable on the dependent variable, write a non-directional (two-tailed) hypothesis.
• Make it Testable : Ensure your hypothesis can be tested through experimentation or observation. It should be possible to prove it false (principle of falsifiability).
• Clear & concise language . A strong hypothesis is concise (typically one to two sentences long), and formulated using clear and straightforward language, ensuring it’s easily understood and testable.

Consider a hypothesis many teachers might subscribe to: students work better on Monday morning than on Friday afternoon (IV=Day, DV= Standard of work).

Now, if we decide to study this by giving the same group of students a lesson on a Monday morning and a Friday afternoon and then measuring their immediate recall of the material covered in each session, we would end up with the following:

• The alternative hypothesis states that students will recall significantly more information on a Monday morning than on a Friday afternoon.
• The null hypothesis states that there will be no significant difference in the amount recalled on a Monday morning compared to a Friday afternoon. Any difference will be due to chance or confounding factors.

More Examples

• Memory : Participants exposed to classical music during study sessions will recall more items from a list than those who studied in silence.
• Social Psychology : Individuals who frequently engage in social media use will report higher levels of perceived social isolation compared to those who use it infrequently.
• Developmental Psychology : Children who engage in regular imaginative play have better problem-solving skills than those who don’t.
• Clinical Psychology : Cognitive-behavioral therapy will be more effective in reducing symptoms of anxiety over a 6-month period compared to traditional talk therapy.
• Cognitive Psychology : Individuals who multitask between various electronic devices will have shorter attention spans on focused tasks than those who single-task.
• Health Psychology : Patients who practice mindfulness meditation will experience lower levels of chronic pain compared to those who don’t meditate.
• Organizational Psychology : Employees in open-plan offices will report higher levels of stress than those in private offices.
• Behavioral Psychology : Rats rewarded with food after pressing a lever will press it more frequently than rats who receive no reward.

Nursing Research Methodology Guide

Nursing research is an art of scientific investigation that aims to solve healthcare problems or nursing issues. It uses disciplined methods to collect and analyze data to develop meaningful findings that help solve problems.

Research helps provide evidence pertinent to making sound decisions in a clinical setting. To properly conduct research, one must select appropriate research methods that facilitate systematic study planning, data collection, and information inquiry. When designing nursing research, you must understand what research methodologies are.

This article will explore research methodologies, why they are essential in nursing, the different types of research methods, and their characteristics.

Importance of Research Methodologies in Nursing Education

Research methodologies outline all the procedures, methods, and techniques used in a research study. They allow for data collection, analysis, and interpretation.

Research methodologies are instrumental in answering questions that are encountered in clinical practice. It details the researcher's valid and reliable approach to fulfilling their goals and objectives.

A sound research methodology can help in providing the following benefits.

• Give other researchers enough information to replicate their research.
• In case of any criticism, the researcher can return to their methodology to explain the approach used.
• Provides a specific plan for researchers to follow.
• It allows researchers to select the proper methods to fulfill their objectives.

Role of Research in Nursing Practice and Education

In nursing, research is the systematic investigation of developing relevant knowledge about issues that are important to nurses, such as practice, education, and administration. Since nurses are healthcare professionals, they do not only work in hospitals.

The scope of nursing practice is broad, and the (nurses) work in different sectors. Some work in teaching, and others in community health, business, government agencies, etc. Hence, the scope of nursing is getting wider, with many responsibilities. The responsibility of taking care of patients is vested in nurses. They deal with nursing problems and know the treatment options required by each patient, which treatment they should focus on, and which to terminate.

Adequately conducted research can provide evidence that helps healthcare professionals provide quality healthcare to patients and support nursing practices.

High-quality research allows professional growth by giving them the most accurate tools and opportunities to advance their nursing specialty.

Nurses had difficulty caring for patients before clinical hospitals or hospices were more specialized. However, now they rely heavily on research findings to reduce mortality risk and improve patient outcomes.

Nursing research of high quality means the study has answered an important question. It also means that the findings have an actual impact in terms of how care will be carried out to patients and teaching nursing students.

Nurses also have to inform their patients about the recent development in healthcare that can help them make informed decisions about their health or that of their loved ones.

Nursing students pursuing the RN and BSN programs can learn how to retrieve data, review, critique, and apply the results from the research.

Some other reasons why research is vital in nursing practice and education include the following:

• Nursing staff can gain more profound knowledge of various topics
• Conduct a careful and comprehensive search on diagnosis and other patient problems
• Come up with new and better ways to take care of the patient
• Improve nursing standards
• Minimize daily nursing challenges
• Update information on various fields where nurses are involved
• To solve day-to-day obstacles

Hence, research is an integral part of nursing practice. Nurses should rely on research to improve their knowledge, answer pertinent patient questions and provide high-quality care to those under their care.

How Research Methodologies Help Nurses Develop Evidence-based Practice

Evidence-based practices use the best available facts and evidence to improve patient care and outcomes. Essentially, it is a holistic process that integrates the following key elements: scientific research, the expertise of a healthcare professional, and the patient's perspective and preferences.

Studies show that patient outcomes improve significantly when nurses do their work in an evidence-based manner.

Nurses must understand research methodologies because they help advance nursing practice. Nurses use these methodologies to collect evidence-based information in decision-making, enhancing medical delivery and care for patients.

Research findings will offer nurses evidence-based data to develop new ways to assess, evaluate and deliver nursing care.

Types of Research Methodologies in Nursing

Research in nursing must be of high quality to yield valuable results. Nurses must have extensive knowledge and apply relevant evidence in their practice. This evidence can sometimes be in the form of research findings, filling the gaps in knowledge and expertise.

The methods primarily used in nursing to collect and analyze research may be qualitative or quantitative. Selecting the preferred methods solely relies on the one conducting the research. These methods inform nursing practice. Some research questions are best studied through qualitative methods, while others work well with quantitative methods.

However, researchers have recently adopted the best and most desirable methods. However, this is not to say that other methods do not work.

All three methods contribute immensely to nursing. Data collected in quantitative research provides a deeper understanding of everything in the social world. Qualitative data helps in understanding people's feelings, thoughts, and behaviors. The mixed method uses both data to gain a much deeper understanding of complex matters.

Mixed Methods Nursing Research

Mixed method research, also known as multimethodology, involves using elements of both qualitative and quantitative research to find answers to research questions. This aims to help you develop a complete picture since it integrates all the benefits of both methods.

In this method, researchers collect qualitative and quantitative data to conduct a study. This method has grown so much in nursing because of the increasing complexity of delivering proper healthcare. Researchers draw the strengths of the two methods and use them to draw perspective on intricate research topics. Using this method can deepen the understanding of all nursing phenomena.

Mixed methods involve purposefully combining methods in data collection, analysis, and interpretation of findings. The key word here is mixing. Remember that mixed research does not just mean collecting qualitative and quantitative data. You must consider how you will integrate them to come up with coherent conclusions.

Characteristics of Mixed-methods Research

As mentioned, mixed methods are all about collecting and analyzing both qualitative and quantitative data. This mixing of data is a unique aspect of mixed-method research. Mixing data allows a researcher to understand more about a problem than using either data alone.

The following are characteristics of mixed research.

• It involves the analysis of both qualitative and quantitative data
• There is the collection of qualitative and quantitative data in response to a hypothesis
• There is a need for convincing and meticulous procedures when using qualitative and quantitative methods of research
• It involves carefully integrating these two data collected by either emerging or embedding them.
• There is the use of a research approach that is based on a theoretical foundation.
• Using a specific mixed-method plan involving a concurrent integration

The following are examples of studies in healthcare that used mixed-method research.

• A Mixed Methods Research Study of Parental Perceptions of Physical Activity and Quality of Life of Children Under Home Lock Down in the COVID-19 Pandemic
• A mixed methods study on evaluating the performance of a multi-strategy national health program to reduce maternal and child health disparities in Haryana, India
• A mixed methods case study exploring the impact of membership in a multi-activity, multicenter community group on the social well-being of older adults

Qualitative Research in Nursing

Qualitative research is collecting, analyzing, and interpreting information about non-numerical data. This data is observed but cannot be measured. It includes opinions, thoughts, feelings, words, and behaviors. This research helps in understanding concepts and thoughts.

Qualitative research is mainly used to understand concepts that are not familiar. In nursing, qualitative research helps in generating evidence and determining patient preferences. It helps provide a deeper understanding of others and interpret their meanings and behaviors.

Generally, one will use qualitative research if one wants to know more about:

• Perceptions
• Representations
• Or anything subjective

Characteristics of Qualitative Research Method

Any good research must start from a reasonable starting position or a theoretical perspective. Quantitative research involves a positivist perspective whereby a researcher objectively and systematically obtains evidence to prove a hypothesis.

The following are characteristics of qualitative research.

• Researchers collect information from the source of the problem. They go where the participants are to collect the data. This information is collected by directly talking to the participants and seeing them in their natural habitat.
• The qualitative researcher is the key instrument. What this means is that they collect information through observation or direct interviews. They do not rely on questionnaires used by other researchers.
• It involves building patterns of information and themes from the ground up. On the other hand, build it up from separate data to a reasonable conclusion.
• Data is collected from multiple sources rather than relying on a single source.
• The researchers strive to understand the meaning of the data collected from the participants instead of summarizing what other researchers have found out.
• Researchers use perspectives such as cultural concepts, gender differences, race, etc., to collect data.
• Researchers make their own interpretations of what they have observed, seen, and heard. Because of this, there are usually different interpretations from researchers.
• Qualitative researchers aim to create a complete picture of the problem or question they are studying.

The following are examples of nursing research that has used qualitative methods are:

• The Work of Breastfeeding Among Women of Low Socioeconomic Status: A Qualitative Meta-synthesis
• Stressors Among Healthcare Workers: A Summative Content Analysis
• End-of-Life Care for Transgender Older Adults

Quantitative Research in Nursing

Quantitative research, also known as empirical research, collects numerical data that helps understand an existing hypothesis. In other words, this research is based on what can be measured accurately and precisely. This method is important because it helps collect and analyze more information. A complex problem can be reduced and restructured to several variables, resulting in factual, reliable, and generalizable data. One must therefore have background knowledge in mathematics and statistical skills.

Generally, researchers should use quantitative research if they aim to understand more about the following:

• Measurable differences
• Or anything else that is objective

Characteristics of Quantitative Research

Quantitative research uses statistics to make sense of something. It also involves making generalizations from data used to test theories about attitudes and behaviors. Quantitative data aims at clarifying any fuzziness that exists in qualitative data. The numerical insights provided will help you formulate a conclusion.

Here are the characteristics of quantitative research.

• All the methods used in collecting data are adequately structured. They also contain items requiring measurability, such as age, highest education, salary range, etc.
• It uses typically structured data collection methods such as polls, surveys, and questionnaires. These methods help draw the preferences of the participants.
• It relies on large sample sizes to collect data. Researchers conduct their study on a large number of participants to ensure reliability.
• Participants in the research are subjected to close-ended questions. Therefore, the results of these findings are less vague and limit the chances of participants providing wrong information.
• The information collected in quantitative research can be used multiple times.
• It uses close-ended questions, which are more specific than open-ended questions. Responses to open-ended questions are specific and scattered. One must have specific skills to select the needed answers.
• The outcomes from quantitative research are always in numerical form. For example, the answers can be presented in percentage form.
• Many researchers use previous research to analyze previous studies' outcomes to develop their own hypotheses.
• The outcomes of the quantitative study are used to provide a generalization for the whole population. This is because the study is conducted on a large sample size.

The following are examples of nursing studies that used quantitative research.

• Quantitative research on the impact of COVID-19 on frontline nursing staff at a military hospital in Saudi Arabia

Steps in Conducting Nursing Research

Research findings help provide a deeper understanding of how to care for patients.

The following are steps that help in conducting high-quality nursing research.

Step 1: Identify the problem / develop a Hypothesis

When conducting research, researchers try to find answers to a problem. Therefore, it is logical that the first step should be to identify the problem and then come up with the research question. For instance, if the goal is to find out whether there is a link between taking milk chocolate and type II diabetes in adults, one can pose the following hypothesis: Adults who take 20mg of chocolate milk every day have a higher chance of getting type 2 diabetes than those who consume only 10mg a day.

Identifying the keywords in your question is important. In this case, Type II diabetes, 20mg more, adults.

One must consider stating the problem clearly and unambiguously. Remember that research problems show unmet healthcare needs and opportunities l to do better.

When identifying a problem, researchers will use the SMART mnemonic .

S – Specific

M – Measurable

A – Achievable

R – Relevant

T – Time Bound

These problems can be sparked by the following:

• Personal experiences of a nurse.
• Socially significant nursing issues affecting a given population.
• An event that occurs in the workplace.
• Personal interactions in a particular study area trigger the need for further investigation.

The problems double up as the topic of your nursing research. You must analyze each problem individually and settle for one that you can manage. The research problem can be any issue that requires a solution and, in this context, it should relate to the nursing profession. You must provide a rationale for the problem and how your study addresses the issues.  

Step 2: Formulating Research Objectives, Hypothesis, and Questions

The second step in the nursing research process entails developing the scope of your research. This can be achieved by formulating research objectives and developing a research question or hypothesis. In the case of nursing research, coming up with a PICOT question or a clinical question is imperative.

A research objective is the clear, concise, and declarative statement a researcher expresses to guide the study. It helps identify and describe the variables and their relationships. It helps bridge the gap between research purpose and design. It also helps guide the data collection and analysis plans. An objective summarizes the intent and scope of the research. It also keeps the researcher focused and helps build a link with the problem statement. It should be SMART.

The research question you select for your research study should be clear and well-defined. You can derive a good research question from a literature search, theoretical frameworks on nursing, and your working experience. Ensure that your clinical research question is feasible, interesting, novel, ethical, and relevant to your field of study, area of specialization, or personal/career interests.

Nursing research might or might not include a hypothesis. A hypothesis is the formulation of the expected relationship between two or more variables in a population. For example, a reasonable hypothesis is:  

Healthcare providers with knowledge of standard screening methods for postpartum depression will help identify symptoms early.

There is a predicted relationship between knowledge of using standard PPD screening methods and early detection of symptoms.

Hypotheses apply to quantitative studies such as quasi-experimental or experimental nursing research studies. Once you test the hypothesis, you can accept or reject it, which you will include in the report write-up.

There are various types of hypotheses:

• Directional hypothesis – predicts the outcome in a specific direction. An example is when you say that persons with Type II Diabetes who have more excellent knowledge of self-management will have higher rates of adherence to treatment and management plans compared to those with no knowledge.
• Non-directional hypothesis – indicates a difference or correlation without being specific. For example, Type II Diabetes Mellitus patients who follow structured self-management programs have a higher chance of treatment adherence. Here, you do not indicate the directional relationship as the directional hypothesis does.
• Null hypothesis (Ho) – states no difference exist between groups or that there is no correlation between variables.
• Alternative hypothesis (H1) – states that there is a difference or correlation between variables.

Variables are qualities, properties, attributes, or characteristics that change or vary, such as age, sex, satisfaction, success, pain, stress, etc.

The independent (treatment or experimental variables) influence other variables. They enable or contribute to an inevitable outcome. It refers to the intervention of treatment the researcher performs to see some change in the dependent variables. It is the input.

The dependent variables are the outcome variables that reflect the independent variable's results, response, outcome, or effect. Majorly, dependent variables receive the action and can disappear, diminish, increase, and appear. When determining the effects of sugar consumption on obesity, obesity is the dependent variable, while sugar consumption is the independent variable.

We also have uncontrolled extraneous variables that influence the research study's findings. They affect the independent and dependent variables. They are referred to as threats of internal and external validity since they might lead to a bias in the selection, time, and instrument used.

Finally, we also have the demographic variables, which are the attributes of a population such as age, sex, religious beliefs, or educational levels that a researcher cannot manipulate.

Step 3: Reviewing the Literature

This is an essential step in the nursing research process. A literature review accounts for what has already been published about a particular research topic.

Conducting a literature review can help provide precise, relevant, and timely information on the topic of interest. It allows one to explore the background of their topic's scientific findings.

Your literature review should show that you are familiar with previous studies for a better interpretation of your results. It should also help you determine if there are new approaches or stimulate you to develop new ideas. The literature review can also help you to review the research topic and determine the knowledge gaps to justify your problem statement.

You should also identify the theoretical frameworks, tools, models, and instruments useful for a research problem.

When writing the literature review, you should consider primary sources. You should also use secondary sources such as scholarly journals, books, conference and seminar papers, theses and dissertations, and government or institutional (organizational) documents.

Some sources for literature review for nursing topics include conference papers, theses, journals, electronic databases, and books.

Related Reading: Literature Review vs. Systematic Reviews

Step 4: Develop a Research Plan

Once the research question has been identified, it is time to develop a study plan. When selecting the most appropriate research method, consider the following:

• Type of research ­that is suitable for the investigation, for example, descriptive, experimental, etc.
• The research design is experimental, survey, descriptive, case study, ethnography, phenomenology, grounded theory, and historical research.
• Details of the data to be collected and all relevant variables.
• Where the samples can best be collected and the techniques to be used.
• All the relevant methods for collecting data, e.g., Polls, observation, questionnaires, etc. One should consider all the aspects that could affect reliability and validity.

A research plan will minimize the time, effort, and money spent acquiring meaningful evidence. A proper plan will help in the following categories:

• Exploration and Surveys
• Data Analysis
• Observation

Step 5: Describe the Sample Population

Population, in this case, refers to the group one intends to study. The research topic will determine the study group selected. Therefore, one must select a topic they are familiar with, one that aligns with their specialization or professional interests, and one they can manage.

When investigating a select group of people in a community, one could target a specific age group, an ethnic group, and a particular geographical location.

Step 6: Collecting Data

Collecting data is vital in getting the information required to provide answers to the raised question. The data is organized into structures to make it easy to execute.

Data must be collected from different sources: primary and secondary.

Primary sources include:

• Focus groups - involve interviewing and observing people
• Questionnaire - asking a group of people a bunch of questions
• Observation - collecting data without asking people questions
• Interview - asking people questions about what they know

Secondary sources are:

• Literature survey
• Reports : Official and unofficial
• Library resources, including old reports, books, etc .

Step 7: Data Analysis

After gathering data, the researcher begins to analyze or interpret the information collected. Data analysis summarizes the collected data to develop patterns or relationships between them. This process involves cleaning, transforming, and modeling data for helpful information.

The steps for analyzing data are as follows.

• Going through the research plan.
• Organizing all the data collected.
• Writing a rough draft of the findings and conclusion. This is important as it will help in organizing one's thoughts.
• Polishing the rough draft to the final findings. A researcher will probably do this several times to ensure the final draft has no errors as they prepare for the final part.

Take note that the goal of the analysis is not to come up with information supporting a hypothesis but to review all data objectively to determine the most accurate. One must ensure this information is easy to understand.

Step 8: Create a Report

A report is a well-written text that shows details about the research conducted. This report is written after the researcher has collected and analyzed all the data about the topic. It is a reliable source for recounting research. One must only include significant findings and avoid irrelevant information when writing it.

Researchers report their findings in either of the following formats:

• Formal Paper (capstone project, QI report, thesis, dissertation, white paper, conference paper, etc.).
• Published Article
• PowerPoint Presentation
• Audio or Video
• Spreadsheet

Take note that this part is crucial. One must effectively explain their research findings clearly and succinctly.

Tips and Resources for Conducting Research

Having the right research skills can be the difference between succeeding or failing in nursing school and every part of a nursing career. Learning how to conduct research is essential since nursing keeps evolving rapidly.

Being successful in nursing means one needs to learn how to use literature, search engines and analyze the collected data. The following tips will help in conducting high-quality research.

1. Choose the Right Research Topic

This is the first step and perhaps the most crucial part of conducting research. One must select a topic that is within the parameters of the assignment. Nursing instructions give students guidelines on what to do and things to avoid. Therefore, students follow these guidelines so that the instructor can accept the final report.

Additionally, one must choose a topic that interests them and one that they are familiar with. Doing this will make the research process enjoyable.

2. Locate the Research Materials

Conducting adequate research means locating all the materials and utilizing all the provided resources. Some resources are available online, while others are available in print. Nursing schools also have access to journals not published on the Internet.

A student should take advantage of what the school offers regarding resources, as it will significantly help in research.

3. Refine the Search Results

When conducting research online, one must filter out any unnecessary resources. Researchers should consider only locating search results relevant to their area of study. They should use Google searches and other nursing literature searchers to narrow down their search results. To locate newspaper articles and magazines, Students should use electronic periodical databases. Additionally, they should only use the database best suited for the chosen topic.

4. Evaluate All the Sources

There is a lot of information on the Internet, and some are not accurate or relevant. Unlike books or print resources, no one has approved some of the information before being made public. Therefore, students must evaluate all their resources to ensure it is of the right quality. The CARS Checklist for Information Quality provides tips on assessing the sources' worth. Remember that the instructor expects highly credible and reliable research findings.

5. Be Prepared for Surprising Answers

High-quality research involves finding answers but not verifying what is already known. So one must keep an open mind when collecting data to learn more.

6. Make Notes

One should note all the relevant information pertinent to your study during research. When collecting information from a specific group of people, researchers must pay attention to what they are saying. In addition, they should use all the data collection methods provided to ensure relevant and reliable data.

7. Cite All Sources

When writing a report, one must cite all the sources used when conducting research. Using in-text citations acknowledges all the sources of information used in your paper. Then at the end of the paper, one must write down the list of all cited sources.

Citing sources is also an excellent way to prevent plagiarism in the work. Therefore, it is crucial to learn how to cite sources in either APA or Harvard format, which are the main formatting styles that nursing schools prefer.

Ethical Considerations When Conducting Research

Ethical considerations are principles guiding the research process and practice. This part is among the most critical parts of research. Researchers must always adhere to a specific code of conduct when collecting data from the population. The research will be doomed if one fails to follow these considerations.

Research ethics matter for integrity, dignity, and human rights. They ensure that aver research is conducted voluntarily and safely for all the participants.

Following all ethical considerations is an essential part of research because of the following reasons.

• It helps critically evaluate all the research work to ensure no apparent errors.
• It allows one to plan their work well to avoid any misleading results and ensure that all the questions on ethical procedures are resolved.
• Ensures that the public can trust their work, thus supporting and funding it.
• Promoting the aims of the research, for instance, expanding knowledge
• Supporting all the required collaborative work ethics such as fairness, mutual respect, etc. This is key because nursing research depends on collaboration between different groups.
• Remaining accountable for all actions taken when conducting research.

Significant Ethical Challenges in Nursing Research

When conducting your research, there are specific challenges one will come across. These can make it harder to complete the research. Three value systems involving research are connected to each other: society, science, and nursing. Therefore, significant ethical issues during research are linked to these three.

The challenges one will likely encounter when carrying out nursing research are:

1. Informed Consent

This means that an individual has knowingly and voluntarily decided to consent. It is a means by which a person's autonomy is protected. Individuals have to make informed decisions before participating in any research in which there are risks involved.

2. Beneficence- Do Not Harm

Also known as "be of benefit, do no harm," this ethical principle means a researcher must do effective and high-quality research to promote the welfare of others better. This can something be challenging, especially when using qualitative research. If proven not beneficial according to the expectations, it can raise significant ethical considerations for nurses.

3. Anonymity and Confidentiality

Anonymity and confidentiality are closely linked to beneficence. A person's anonymity is guaranteed when their identity is not linked to personal responses if you cannot guarantee anonymity to the subjects.

Confidentiality means that participants are free to withhold their information as they please. It becomes a dilemma when one has to break confidentiality to share important information.

4. Research Integrity

Working in a research environment means facing a highly competitive and performance-based environment. While this is good, it can lead to researchers engaging in unethical issues, reflecting a lack of integrity.

5. Conflict of Interest

Nurses and the institutions involved in research have varied interests, which can sometimes lead to conflicts. The conflicts can arise from different sources, such as interpersonal conflicts, holding multiple roles, financial issues, third-party pressures, etc.

Final Remarks on Nursing Research Methodology

Research in nursing is essential in finding and improving the different ways of treating and caring for patients. Nurses are the ones who know patients best. They understand what is working for them and what is not.  Research findings inform decision-making and advance nursing practice. Research methodology provides a detailed plan, keeping nurses on track and ensuring the process is smooth and effective.

In designing a research methodology, one must consider the research objectives. Knowing what information is expected at the end of the study will make it much easier to select the suitable methodology. Additionally, one must consider the nature of the research. If the goal is exploratory, qualitative research methods should be chosen. On the other hand, choosing the quantitative method is a good idea if the goal is to measure something. However, to understand a problem much better, one must combine both methods in mixed-method research.

If you are doing your undergraduate, MSN, DNP, or Ph.D. level nursing dissertation, capstone project, or thesis and need help, we have the best graduate-level nursing writers . Place an order today and get 100% confidential help, original papers, and direct access to your writer.

Struggling with

Related Articles

Hardest Nursing Classes and How to Pass Them Well

Middle-Range Nursing Theories

iHuman Tips and Tricks for Success

NurseMyGrades is being relied upon by thousands of students worldwide to ace their nursing studies. We offer high quality sample papers that help students in their revision as well as helping them remain abreast of what is expected of them.

13 Different Types of Hypothesis

There are 13 different types of hypothesis. These include simple, complex, null, alternative, composite, directional, non-directional, logical, empirical, statistical, associative, exact, and inexact.

A hypothesis can be categorized into one or more of these types. However, some are mutually exclusive and opposites. Simple and complex hypotheses are mutually exclusive, as are direction and non-direction, and null and alternative hypotheses.

Below I explain each hypothesis in simple terms for absolute beginners. These definitions may be too simple for some, but they’re designed to be clear introductions to the terms to help people wrap their heads around the concepts early on in their education about research methods .

Types of Hypothesis

Before you Proceed: Dependent vs Independent Variables

A research study and its hypotheses generally examine the relationships between independent and dependent variables – so you need to know these two concepts:

• The independent variable is the variable that is causing a change.
• The dependent variable is the variable the is affected by the change. This is the variable being tested.

Read my full article on dependent vs independent variables for more examples.

Example: Eating carrots (independent variable) improves eyesight (dependent variable).

1. Simple Hypothesis

A simple hypothesis is a hypothesis that predicts a correlation between two test variables: an independent and a dependent variable.

This is the easiest and most straightforward type of hypothesis. You simply need to state an expected correlation between the dependant variable and the independent variable.

You do not need to predict causation (see: directional hypothesis). All you would need to do is prove that the two variables are linked.

Simple Hypothesis Examples

2. complex hypothesis.

A complex hypothesis is a hypothesis that contains multiple variables, making the hypothesis more specific but also harder to prove.

You can have multiple independent and dependant variables in this hypothesis.

Complex Hypothesis Example

In the above example, we have multiple independent and dependent variables:

• Independent variables: Age and weight.
• Dependent variables: diabetes and heart disease.

Because there are multiple variables, this study is a lot more complex than a simple hypothesis. It quickly gets much more difficult to prove these hypotheses. This is why undergraduate and first-time researchers are usually encouraged to use simple hypotheses.

3. Null Hypothesis

A null hypothesis will predict that there will be no significant relationship between the two test variables.

For example, you can say that “The study will show that there is no correlation between marriage and happiness.”

A good way to think about a null hypothesis is to think of it in the same way as “innocent until proven guilty”[1]. Unless you can come up with evidence otherwise, your null hypothesis will stand.

A null hypothesis may also highlight that a correlation will be inconclusive . This means that you can predict that the study will not be able to confirm your results one way or the other. For example, you can say “It is predicted that the study will be unable to confirm a correlation between the two variables due to foreseeable interference by a third variable .”

Beware that an inconclusive null hypothesis may be questioned by your teacher. Why would you conduct a test that you predict will not provide a clear result? Perhaps you should take a closer look at your methodology and re-examine it. Nevertheless, inconclusive null hypotheses can sometimes have merit.

Null Hypothesis Examples

4. alternative hypothesis.

An alternative hypothesis is a hypothesis that is anything other than the null hypothesis. It will disprove the null hypothesis.

We use the symbol H A or H 1 to denote an alternative hypothesis.

The null and alternative hypotheses are usually used together. We will say the null hypothesis is the case where a relationship between two variables is non-existent. The alternative hypothesis is the case where there is a relationship between those two variables.

The following statement is always true: H 0 ≠ H A .

Let’s take the example of the hypothesis: “Does eating oatmeal before an exam impact test scores?”

We can have two hypotheses here:

• Null hypothesis (H 0 ): “Eating oatmeal before an exam does not impact test scores.”
• Alternative hypothesis (H A ): “Eating oatmeal before an exam does impact test scores.”

For the alternative hypothesis to be true, all we have to do is disprove the null hypothesis for the alternative hypothesis to be true. We do not need an exact prediction of how much oatmeal will impact the test scores or even if the impact is positive or negative. So long as the null hypothesis is proven to be false, then the alternative hypothesis is proven to be true.

5. Composite Hypothesis

A composite hypothesis is a hypothesis that does not predict the exact parameters, distribution, or range of the dependent variable.

Often, we would predict an exact outcome. For example: “23 year old men are on average 189cm tall.” Here, we are giving an exact parameter. So, the hypothesis is not composite.

But, often, we cannot exactly hypothesize something. We assume that something will happen, but we’re not exactly sure what. In these cases, we might say: “23 year old men are not on average 189cm tall.”

We haven’t set a distribution range or exact parameters of the average height of 23 year old men. So, we’ve introduced a composite hypothesis as opposed to an exact hypothesis.

Generally, an alternative hypothesis (discussed above) is composite because it is defined as anything except the null hypothesis. This ‘anything except’ does not define parameters or distribution, and therefore it’s an example of a composite hypothesis.

6. Directional Hypothesis

A directional hypothesis makes a prediction about the positivity or negativity of the effect of an intervention prior to the test being conducted.

Instead of being agnostic about whether the effect will be positive or negative, it nominates the effect’s directionality.

We often call this a one-tailed hypothesis (in contrast to a two-tailed or non-directional hypothesis) because, looking at a distribution graph, we’re hypothesizing that the results will lean toward one particular tail on the graph – either the positive or negative.

Directional Hypothesis Examples

7. non-directional hypothesis.

A non-directional hypothesis does not specify the predicted direction (e.g. positivity or negativity) of the effect of the independent variable on the dependent variable.

These hypotheses predict an effect, but stop short of saying what that effect will be.

A non-directional hypothesis is similar to composite and alternative hypotheses. All three types of hypothesis tend to make predictions without defining a direction. In a composite hypothesis, a specific prediction is not made (although a general direction may be indicated, so the overlap is not complete). For an alternative hypothesis, you often predict that the even will be anything but the null hypothesis, which means it could be more or less than H 0 (or in other words, non-directional).

Let’s turn the above directional hypotheses into non-directional hypotheses.

Non-Directional Hypothesis Examples

8. logical hypothesis.

A logical hypothesis is a hypothesis that cannot be tested, but has some logical basis underpinning our assumptions.

These are most commonly used in philosophy because philosophical questions are often untestable and therefore we must rely on our logic to formulate logical theories.

Usually, we would want to turn a logical hypothesis into an empirical one through testing if we got the chance. Unfortunately, we don’t always have this opportunity because the test is too complex, expensive, or simply unrealistic.

Here are some examples:

• Before the 1980s, it was hypothesized that the Titanic came to its resting place at 41° N and 49° W, based on the time the ship sank and the ship’s presumed path across the Atlantic Ocean. However, due to the depth of the ocean, it was impossible to test. Thus, the hypothesis was simply a logical hypothesis.
• Dinosaurs closely related to Aligators probably had green scales because Aligators have green scales. However, as they are all extinct, we can only rely on logic and not empirical data.

9. Empirical Hypothesis

An empirical hypothesis is the opposite of a logical hypothesis. It is a hypothesis that is currently being tested using scientific analysis. We can also call this a ‘working hypothesis’.

We can to separate research into two types: theoretical and empirical. Theoretical research relies on logic and thought experiments. Empirical research relies on tests that can be verified by observation and measurement.

So, an empirical hypothesis is a hypothesis that can and will be tested.

• Raising the wage of restaurant servers increases staff retention.
• Adding 1 lb of corn per day to cows’ diets decreases their lifespan.
• Mushrooms grow faster at 22 degrees Celsius than 27 degrees Celsius.

Each of the above hypotheses can be tested, making them empirical rather than just logical (aka theoretical).

10. Statistical Hypothesis

A statistical hypothesis utilizes representative statistical models to draw conclusions about broader populations.

It requires the use of datasets or carefully selected representative samples so that statistical inference can be drawn across a larger dataset.

This type of research is necessary when it is impossible to assess every single possible case. Imagine, for example, if you wanted to determine if men are taller than women. You would be unable to measure the height of every man and woman on the planet. But, by conducting sufficient random samples, you would be able to predict with high probability that the results of your study would remain stable across the whole population.

You would be right in guessing that almost all quantitative research studies conducted in academic settings today involve statistical hypotheses.

Statistical Hypothesis Examples

• Human Sex Ratio. The most famous statistical hypothesis example is that of John Arbuthnot’s sex at birth case study in 1710. Arbuthnot used birth data to determine with high statistical probability that there are more male births than female births. He called this divine providence, and to this day, his findings remain true: more men are born than women.
• Lady Testing Tea. A 1935 study by Ronald Fisher involved testing a woman who believed she could tell whether milk was added before or after water to a cup of tea. Fisher gave her 4 cups in which one randomly had milk placed before the tea. He repeated the test 8 times. The lady was correct each time. Fisher found that she had a 1 in 70 chance of getting all 8 test correct, which is a statistically significant result.

11. Associative Hypothesis

An associative hypothesis predicts that two variables are linked but does not explore whether one variable directly impacts upon the other variable.

We commonly refer to this as “ correlation does not mean causation ”. Just because there are a lot of sick people in a hospital, it doesn’t mean that the hospital made the people sick. There is something going on there that’s causing the issue (sick people are flocking to the hospital).

So, in an associative hypothesis, you note correlation between an independent and dependent variable but do not make a prediction about how the two interact. You stop short of saying one thing causes another thing.

Associative Hypothesis Examples

• Sick people in hospital. You could conduct a study hypothesizing that hospitals have more sick people in them than other institutions in society. However, you don’t hypothesize that the hospitals caused the sickness.
• Lice make you healthy. In the Middle Ages, it was observed that sick people didn’t tend to have lice in their hair. The inaccurate conclusion was that lice was not only a sign of health, but that they made people healthy. In reality, there was an association here, but not causation. The fact was that lice were sensitive to body temperature and fled bodies that had fevers.

12. Causal Hypothesis

A causal hypothesis predicts that two variables are not only associated, but that changes in one variable will cause changes in another.

A causal hypothesis is harder to prove than an associative hypothesis because the cause needs to be definitively proven. This will often require repeating tests in controlled environments with the researchers making manipulations to the independent variable, or the use of control groups and placebo effects .

If we were to take the above example of lice in the hair of sick people, researchers would have to put lice in sick people’s hair and see if it made those people healthier. Researchers would likely observe that the lice would flee the hair, but the sickness would remain, leading to a finding of association but not causation.

Causal Hypothesis Examples

13. exact vs. inexact hypothesis.

For brevity’s sake, I have paired these two hypotheses into the one point. The reality is that we’ve already seen both of these types of hypotheses at play already.

An exact hypothesis (also known as a point hypothesis) specifies a specific prediction whereas an inexact hypothesis assumes a range of possible values without giving an exact outcome. As Helwig [2] argues:

“An “exact” hypothesis specifies the exact value(s) of the parameter(s) of interest, whereas an “inexact” hypothesis specifies a range of possible values for the parameter(s) of interest.”

Generally, a null hypothesis is an exact hypothesis whereas alternative, composite, directional, and non-directional hypotheses are all inexact.

See Next: 15 Hypothesis Examples

This is introductory information that is basic and indeed quite simplified for absolute beginners. It’s worth doing further independent research to get deeper knowledge of research methods and how to conduct an effective research study. And if you’re in education studies, don’t miss out on my list of the best education studies dissertation ideas .

[1] https://jnnp.bmj.com/content/91/6/571.abstract

[2] http://users.stat.umn.edu/~helwig/notes/SignificanceTesting.pdf

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 5 Top Tips for Succeeding at University
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 50 Durable Goods Examples
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 100 Consumer Goods Examples
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 30 Globalization Pros and Cons

2 thoughts on “13 Different Types of Hypothesis”

Wow! This introductionary materials are very helpful. I teach the begginers in research for the first time in my career. The given tips and materials are very helpful. Chris, thank you so much! Excellent materials!

You’re more than welcome! If you want a pdf version of this article to provide for your students to use as a weekly reading on in-class discussion prompt for seminars, just drop me an email in the Contact form and I’ll get one sent out to you.

When I’ve taught this seminar, I’ve put my students into groups, cut these definitions into strips, and handed them out to the groups. Then I get them to try to come up with hypotheses that fit into each ‘type’. You can either just rotate hypothesis types so they get a chance at creating a hypothesis of each type, or get them to “teach” their hypothesis type and examples to the class at the end of the seminar.

Cheers, Chris

Leave a Comment Cancel Reply

Your email address will not be published. Required fields are marked *

Trends in hypothesis testing and related variables in nursing research: a retrospective exploratory study

Affiliation.

• 1 Northern Illinois University, DeKalb, IL, USA. [email protected]
• PMID: 21560925
• DOI: 10.7748/nr2011.04.18.3.38.c8462

Aim: To compare the inclusion and the influences of selected variables on hypothesis testing during the 1980s and 1990s.

Background: In spite of the emphasis on conducting inquiry consistent with the tenets of logical positivism, there have been no studies investigating the frequency and patterns of hypothesis testing in nursing research

Data sources: The sample was obtained from the journal Nursing Research which was the research journal with the highest circulation during the study period under study. All quantitative studies published during the two decades including briefs and historical studies were included in the analyses

Review methods: A retrospective design was used to select the sample. Five years from the 1980s and 1990s each were randomly selected from the journal, Nursing Research. Of the 582 studies, 517 met inclusion criteria.

Discussion: Findings suggest that there has been a decline in the use of hypothesis testing in the last decades of the 20th century. Further research is needed to identify the factors that influence the conduction of research with hypothesis testing.

Conclusion: Hypothesis testing in nursing research showed a steady decline from the 1980s to 1990s. Research purposes of explanation, and prediction/ control increased the likelihood of hypothesis testing.

Implications for practice: Hypothesis testing strengthens the quality of the quantitative studies, increases the generality of findings and provides dependable knowledge. This is particularly true for quantitative studies that aim to explore, explain and predict/control phenomena and/or test theories. The findings also have implications for doctoral programmes, research preparation of nurse-investigators, and theory testing.

• Nursing Research*
• Retrospective Studies

Ask a question from expert

Nursing Research: Importance, Hypothesis, Sampling, Ethics, and Scientific Method

Answer multiple choice questions related to nursing research.

Added on   2023-06-04

About This Document

   Added on  2023-06-04

End of preview

Want to access all the pages? Upload your documents or become a member.

Evidence Based Nursing Research lg ...

Predicting factors of depression and anxiety in mental health nurses lg ..., article analysis and evaluation of research ethics lg ..., nursing research and quantitative studies lg ..., quantitative critique rubric lg ..., self‐weighing and simple dietary advice for overweight and obese pregnant lg ....

International Journal of Nursing Science Practice and Research

• Other Journals
• For Readers
• For Authors
• For Librarians
• Announcements
• JournalsPub Home Page
• Editorial Board
• Publication Ethics & Malpractice Statement

Hypothesis Types and Research

Dennis F. Polit. Nursing Research: Generating and Assessing Evidence for Nursing Practice, 9th edition. New Delhi: Lippincott Williams and Wilkins; 2012, 58–93p.

Nursing Research society of India, Nursing research and statistics, 1st edition. India: Pearson Publication; 2013, 48–51p.

Polit DF, Hungler BP. Nursing Research Principles and Methods. Philadelphia: Lippincott; 1999.

• There are currently no refbacks.