what is hypothesis in research proposal

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 .

Prevent plagiarism. Run a free check.

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 15, 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, what is your plagiarism score.

• 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)

Have a language expert improve your writing

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

• Knowledge Base
• Methodology
• How to Write a Strong Hypothesis | Guide & Examples

How to Write a Strong Hypothesis | Guide & Examples

Published on 6 May 2022 by Shona McCombes .

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.

Table of contents

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, 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 variables . An independent variable is something the researcher changes or controls. A dependent variable is something the researcher observes and measures.

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 .

Prevent plagiarism, run a free check.

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 identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalise 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.

Step 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

Step 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.

Step 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 .

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.

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).

A research hypothesis is your proposed answer to your research question. The research hypothesis usually includes an explanation (‘ x affects y because …’).

A statistical hypothesis, on the other hand, is a mathematical statement about a population parameter. Statistical hypotheses always come in pairs: the null and alternative hypotheses. In a well-designed study , the statistical hypotheses correspond logically to the research hypothesis.

Cite this Scribbr article

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

McCombes, S. (2022, May 06). How to Write a Strong Hypothesis | Guide & Examples. Scribbr. Retrieved 15 April 2024, from https://www.scribbr.co.uk/research-methods/hypothesis-writing/

Is this article helpful?

Shona McCombes

Other students also liked, operationalisation | a guide with examples, pros & cons, what is a conceptual framework | tips & examples, a quick guide to experimental design | 5 steps & examples.

• Bipolar Disorder
• Therapy Center
• When To See a Therapist
• Types of Therapy
• Best Online Therapy
• Best Couples Therapy
• Best Family Therapy
• Managing Stress
• Sleep and Dreaming
• Understanding Emotions
• Self-Improvement
• Healthy Relationships
• Student Resources
• Personality Types
• Guided Meditations
• Verywell Mind Insights
• 2023 Verywell Mind 25
• Mental Health in the Classroom
• Editorial Process
• Meet Our Review Board
• Crisis Support

How to Write a Great Hypothesis

Hypothesis Format, Examples, and Tips

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Amy Morin, LCSW, is a psychotherapist and international bestselling author. Her books, including "13 Things Mentally Strong People Don't Do," have been translated into more than 40 languages. Her TEDx talk,  "The Secret of Becoming Mentally Strong," is one of the most viewed talks of all time.

Verywell / Alex Dos Diaz

• The Scientific Method

Hypothesis Format

Falsifiability of a hypothesis, operational definitions, types of hypotheses, hypotheses examples.

• Collecting Data

Frequently Asked Questions

A hypothesis is a tentative statement about the relationship between two or more  variables. It is a specific, testable prediction about what you expect to happen in a study.

One hypothesis example would be a study designed to look at the relationship between sleep deprivation and test performance might have a hypothesis that states: "This study is designed to assess the hypothesis that sleep-deprived people will perform worse on a test than individuals who are not sleep-deprived."

This article explores how a hypothesis is used in psychology research, how to write a good hypothesis, and the different types of hypotheses you might use.

The Hypothesis in the Scientific Method

In the scientific method , whether it involves research in psychology, biology, or some other area, a hypothesis represents what the researchers think will happen in an experiment. The scientific method involves the following steps:

• Forming a question
• Performing background research
• Creating a hypothesis
• Designing an experiment
• Collecting data
• Analyzing the results
• Drawing conclusions
• Communicating the results

The hypothesis is a prediction, but it involves more than a guess. Most of the time, the hypothesis begins with a question which is then explored through background research. It is only at this point that researchers begin to develop a testable hypothesis. Unless you are creating an exploratory study, your hypothesis should always explain what you  expect  to happen.

In a study exploring the effects of a particular drug, the hypothesis might be that researchers expect the drug to have some type of effect on the symptoms of a specific illness. In psychology, the hypothesis might focus on how a certain aspect of the environment might influence a particular behavior.

Remember, a hypothesis does not have to be correct. While the hypothesis predicts what the researchers expect to see, the goal of the research is to determine whether this guess is right or wrong. When conducting an experiment, researchers might explore a number of factors to determine which ones might contribute to the ultimate outcome.

In many cases, researchers may find that the results of an experiment  do not  support the original hypothesis. When writing up these results, the researchers might suggest other options that should be explored in future studies.

In many cases, researchers might draw a hypothesis from a specific theory or build on previous research. For example, prior research has shown that stress can impact the immune system. So a researcher might hypothesize: "People with high-stress levels will be more likely to contract a common cold after being exposed to the virus than people who have low-stress levels."

In other instances, researchers might look at commonly held beliefs or folk wisdom. "Birds of a feather flock together" is one example of folk wisdom that a psychologist might try to investigate. The researcher might pose a specific hypothesis that "People tend to select romantic partners who are similar to them in interests and educational level."

Elements of a Good Hypothesis

So how do you write a good hypothesis? When trying to come up with a hypothesis for your research or experiments, ask yourself the following questions:

• Is your hypothesis based on your research on a topic?
• Can your hypothesis be tested?
• Does your hypothesis include independent and dependent variables?

Before you come up with a specific hypothesis, spend some time doing background research. Once you have completed a literature review, start thinking about potential questions you still have. Pay attention to the discussion section in the  journal articles you read . Many authors will suggest questions that still need to be explored.

To form a hypothesis, you should take these steps:

• Collect as many observations about a topic or problem as you can.
• Evaluate these observations and look for possible causes of the problem.
• Create a list of possible explanations that you might want to explore.
• After you have developed some possible hypotheses, think of ways that you could confirm or disprove each hypothesis through experimentation. This is known as falsifiability.

In the scientific method ,  falsifiability is an important part of any valid hypothesis.   In order to test a claim scientifically, it must be possible that the claim could be proven false.

Students sometimes confuse the idea of falsifiability with the idea that it means that something is false, which is not the case. What falsifiability means is that  if  something was false, then it is possible to demonstrate that it is false.

One of the hallmarks of pseudoscience is that it makes claims that cannot be refuted or proven false.

A variable is a factor or element that can be changed and manipulated in ways that are observable and measurable. However, the researcher must also define how the variable will be manipulated and measured in the study.

For example, a researcher might operationally define the variable " test anxiety " as the results of a self-report measure of anxiety experienced during an exam. A "study habits" variable might be defined by the amount of studying that actually occurs as measured by time.

These precise descriptions are important because many things can be measured in a number of different ways. One of the basic principles of any type of scientific research is that the results must be replicable.   By clearly detailing the specifics of how the variables were measured and manipulated, other researchers can better understand the results and repeat the study if needed.

Some variables are more difficult than others to define. How would you operationally define a variable such as aggression ? For obvious ethical reasons, researchers cannot create a situation in which a person behaves aggressively toward others.

In order to measure this variable, the researcher must devise a measurement that assesses aggressive behavior without harming other people. In this situation, the researcher might utilize a simulated task to measure aggressiveness.

Hypothesis Checklist

• Does your hypothesis focus on something that you can actually test?
• Does your hypothesis include both an independent and dependent variable?
• Can you manipulate the variables?
• Can your hypothesis be tested without violating ethical standards?

The hypothesis you use will depend on what you are investigating and hoping to find. Some of the main types of hypotheses that you might use include:

• Simple hypothesis : This type of hypothesis suggests that there is a relationship between one independent variable and one dependent variable.
• Complex hypothesis : This type of hypothesis suggests a relationship between three or more variables, such as two independent variables and a dependent variable.
• Null hypothesis : This hypothesis suggests no relationship exists between two or more variables.
• Alternative hypothesis : This hypothesis states the opposite of the null hypothesis.
• Statistical hypothesis : This hypothesis uses statistical analysis to evaluate a representative sample of the population and then generalizes the findings to the larger group.
• Logical hypothesis : This hypothesis assumes a relationship between variables without collecting data or evidence.

A hypothesis often follows a basic format of "If {this happens} then {this will happen}." One way to structure your hypothesis is to describe what will happen to the  dependent variable  if you change the  independent variable .

The basic format might be: "If {these changes are made to a certain independent variable}, then we will observe {a change in a specific dependent variable}."

A few examples of simple hypotheses:

• "Students who eat breakfast will perform better on a math exam than students who do not eat breakfast."
• Complex hypothesis: "Students who experience test anxiety before an English exam will get lower scores than students who do not experience test anxiety."​
• "Motorists who talk on the phone while driving will be more likely to make errors on a driving course than those who do not talk on the phone."

Examples of a complex hypothesis include:

• "People with high-sugar diets and sedentary activity levels are more likely to develop depression."
• "Younger people who are regularly exposed to green, outdoor areas have better subjective well-being than older adults who have limited exposure to green spaces."

Examples of a null hypothesis include:

• "Children who receive a new reading intervention will have scores different than students who do not receive the intervention."
• "There will be no difference in scores on a memory recall task between children and adults."

Examples of an alternative hypothesis:

• "Children who receive a new reading intervention will perform better than students who did not receive the intervention."
• "Adults will perform better on a memory task than children." 

Collecting Data on Your Hypothesis

Once a researcher has formed a testable hypothesis, the next step is to select a research design and start collecting data. The research method depends largely on exactly what they are studying. There are two basic types of research methods: descriptive research and experimental research.

Descriptive Research Methods

Descriptive research such as  case studies ,  naturalistic observations , and surveys are often used when it would be impossible or difficult to  conduct an experiment . These methods are best used to describe different aspects of a behavior or psychological phenomenon.

Once a researcher has collected data using descriptive methods, a correlational study can then be used to look at how the variables are related. This type of research method might be used to investigate a hypothesis that is difficult to test experimentally.

Experimental Research Methods

Experimental methods  are used to demonstrate causal relationships between variables. In an experiment, the researcher systematically manipulates a variable of interest (known as the independent variable) and measures the effect on another variable (known as the dependent variable).

Unlike correlational studies, which can only be used to determine if there is a relationship between two variables, experimental methods can be used to determine the actual nature of the relationship—whether changes in one variable actually  cause  another to change.

A Word From Verywell

The hypothesis is a critical part of any scientific exploration. It represents what researchers expect to find in a study or experiment. In situations where the hypothesis is unsupported by the research, the research still has value. Such research helps us better understand how different aspects of the natural world relate to one another. It also helps us develop new hypotheses that can then be tested in the future.

Some examples of how to write a hypothesis include:

• "Staying up late will lead to worse test performance the next day."
• "People who consume one apple each day will visit the doctor fewer times each year."
• "Breaking study sessions up into three 20-minute sessions will lead to better test results than a single 60-minute study session."

The four parts of a hypothesis are:

• The research question
• The independent variable (IV)
• The dependent variable (DV)
• The proposed relationship between the IV and DV

Castillo M. The scientific method: a need for something better? . AJNR Am J Neuroradiol. 2013;34(9):1669-71. doi:10.3174/ajnr.A3401

Nevid J. Psychology: Concepts and Applications. Wadworth, 2013.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

• Manuscript Preparation

What is and How to Write a Good Hypothesis in Research?

• 4 minute read
• 294.6K views

Table of Contents

One of the most important aspects of conducting research is constructing a strong hypothesis. But what makes a hypothesis in research effective? In this article, we’ll look at the difference between a hypothesis and a research question, as well as the elements of a good hypothesis in research. We’ll also include some examples of effective hypotheses, and what pitfalls to avoid.

What is a Hypothesis in Research?

Simply put, a hypothesis is a research question that also includes the predicted or expected result of the research. Without a hypothesis, there can be no basis for a scientific or research experiment. As such, it is critical that you carefully construct your hypothesis by being deliberate and thorough, even before you set pen to paper. Unless your hypothesis is clearly and carefully constructed, any flaw can have an adverse, and even grave, effect on the quality of your experiment and its subsequent results.

Research Question vs Hypothesis

It’s easy to confuse research questions with hypotheses, and vice versa. While they’re both critical to the Scientific Method, they have very specific differences. Primarily, a research question, just like a hypothesis, is focused and concise. But a hypothesis includes a prediction based on the proposed research, and is designed to forecast the relationship of and between two (or more) variables. Research questions are open-ended, and invite debate and discussion, while hypotheses are closed, e.g. “The relationship between A and B will be C.”

A hypothesis is generally used if your research topic is fairly well established, and you are relatively certain about the relationship between the variables that will be presented in your research. Since a hypothesis is ideally suited for experimental studies, it will, by its very existence, affect the design of your experiment. The research question is typically used for new topics that have not yet been researched extensively. Here, the relationship between different variables is less known. There is no prediction made, but there may be variables explored. The research question can be casual in nature, simply trying to understand if a relationship even exists, descriptive or comparative.

How to Write Hypothesis in Research

Writing an effective hypothesis starts before you even begin to type. Like any task, preparation is key, so you start first by conducting research yourself, and reading all you can about the topic that you plan to research. From there, you’ll gain the knowledge you need to understand where your focus within the topic will lie.

Remember that a hypothesis is a prediction of the relationship that exists between two or more variables. Your job is to write a hypothesis, and design the research, to “prove” whether or not your prediction is correct. A common pitfall is to use judgments that are subjective and inappropriate for the construction of a hypothesis. It’s important to keep the focus and language of your hypothesis objective.

An effective hypothesis in research is clearly and concisely written, and any terms or definitions clarified and defined. Specific language must also be used to avoid any generalities or assumptions.

Use the following points as a checklist to evaluate the effectiveness of your research hypothesis:

• Predicts the relationship and outcome
• Simple and concise – avoid wordiness
• Clear with no ambiguity or assumptions about the readers’ knowledge
• Observable and testable results
• Relevant and specific to the research question or problem

Research Hypothesis Example

Perhaps the best way to evaluate whether or not your hypothesis is effective is to compare it to those of your colleagues in the field. There is no need to reinvent the wheel when it comes to writing a powerful research hypothesis. As you’re reading and preparing your hypothesis, you’ll also read other hypotheses. These can help guide you on what works, and what doesn’t, when it comes to writing a strong research hypothesis.

Here are a few generic examples to get you started.

Eating an apple each day, after the age of 60, will result in a reduction of frequency of physician visits.

Budget airlines are more likely to receive more customer complaints. A budget airline is defined as an airline that offers lower fares and fewer amenities than a traditional full-service airline. (Note that the term “budget airline” is included in the hypothesis.

Workplaces that offer flexible working hours report higher levels of employee job satisfaction than workplaces with fixed hours.

Each of the above examples are specific, observable and measurable, and the statement of prediction can be verified or shown to be false by utilizing standard experimental practices. It should be noted, however, that often your hypothesis will change as your research progresses.

Language Editing Plus

Elsevier’s Language Editing Plus service can help ensure that your research hypothesis is well-designed, and articulates your research and conclusions. Our most comprehensive editing package, you can count on a thorough language review by native-English speakers who are PhDs or PhD candidates. We’ll check for effective logic and flow of your manuscript, as well as document formatting for your chosen journal, reference checks, and much more.

• Research Process

Systematic Literature Review or Literature Review?

What is a Problem Statement? [with examples]

You may also like.

Make Hook, Line, and Sinker: The Art of Crafting Engaging Introductions

Can Describing Study Limitations Improve the Quality of Your Paper?

A Guide to Crafting Shorter, Impactful Sentences in Academic Writing

6 Steps to Write an Excellent Discussion in Your Manuscript

How to Write Clear and Crisp Civil Engineering Papers? Here are 5 Key Tips to Consider

The Clear Path to An Impactful Paper: ②

The Essentials of Writing to Communicate Research in Medicine

Changing Lines: Sentence Patterns in Academic Writing

Input your search keywords and press Enter.

How to Write a Research Hypothesis

• Research Process
• Peer Review

Since grade school, we've all been familiar with hypotheses. The hypothesis is an essential step of the scientific method. But what makes an effective research hypothesis, how do you create one, and what types of hypotheses are there? We answer these questions and more.

Updated on April 27, 2022

What is a research hypothesis?

General hypothesis.

Since grade school, we've all been familiar with the term “hypothesis.” A hypothesis is a fact-based guess or prediction that has not been proven. It is an essential step of the scientific method. The hypothesis of a study is a drive for experimentation to either prove the hypothesis or dispute it.

Research Hypothesis

A research hypothesis is more specific than a general hypothesis. It is an educated, expected prediction of the outcome of a study that is testable.

What makes an effective research hypothesis?

A good research hypothesis is a clear statement of the relationship between a dependent variable(s) and independent variable(s) relevant to the study that can be disproven.

Research hypothesis checklist

Once you've written a possible hypothesis, make sure it checks the following boxes:

• It must be testable: You need a means to prove your hypothesis. If you can't test it, it's not a hypothesis.
• It must include a dependent and independent variable: At least one independent variable ( cause ) and one dependent variable ( effect ) must be included.
• The language must be easy to understand: Be as clear and concise as possible. Nothing should be left to interpretation.
• It must be relevant to your research topic: You probably shouldn't be talking about cats and dogs if your research topic is outer space. Stay relevant to your topic.

How to create an effective research hypothesis

Pose it as a question first.

Start your research hypothesis from a journalistic approach. Ask one of the five W's: Who, what, when, where, or why.

A possible initial question could be: Why is the sky blue?

Do the preliminary research

Once you have a question in mind, read research around your topic. Collect research from academic journals.

If you're looking for information about the sky and why it is blue, research information about the atmosphere, weather, space, the sun, etc.

Write a draft hypothesis

Once you're comfortable with your subject and have preliminary knowledge, create a working hypothesis. Don't stress much over this. Your first hypothesis is not permanent. Look at it as a draft.

Your first draft of a hypothesis could be: Certain molecules in the Earth's atmosphere are responsive to the sky being the color blue.

Make your working draft perfect

Take your working hypothesis and make it perfect. Narrow it down to include only the information listed in the “Research hypothesis checklist” above.

Now that you've written your working hypothesis, narrow it down. Your new hypothesis could be: Light from the sun hitting oxygen molecules in the sky makes the color of the sky appear blue.

Write a null hypothesis

Your null hypothesis should be the opposite of your research hypothesis. It should be able to be disproven by your research.

In this example, your null hypothesis would be: Light from the sun hitting oxygen molecules in the sky does not make the color of the sky appear blue.

Why is it important to have a clear, testable hypothesis?

One of the main reasons a manuscript can be rejected from a journal is because of a weak hypothesis. “Poor hypothesis, study design, methodology, and improper use of statistics are other reasons for rejection of a manuscript,” says Dr. Ish Kumar Dhammi and Dr. Rehan-Ul-Haq in Indian Journal of Orthopaedics.

According to Dr. James M. Provenzale in American Journal of Roentgenology , “The clear declaration of a research question (or hypothesis) in the Introduction is critical for reviewers to understand the intent of the research study. It is best to clearly state the study goal in plain language (for example, “We set out to determine whether condition x produces condition y.”) An insufficient problem statement is one of the more common reasons for manuscript rejection.”

Characteristics that make a hypothesis weak include:

• Unclear variables
• Unoriginality
• Too general
• Too specific

A weak hypothesis leads to weak research and methods . The goal of a paper is to prove or disprove a hypothesis - or to prove or disprove a null hypothesis. If the hypothesis is not a dependent variable of what is being studied, the paper's methods should come into question.

A strong hypothesis is essential to the scientific method. A hypothesis states an assumed relationship between at least two variables and the experiment then proves or disproves that relationship with statistical significance. Without a proven and reproducible relationship, the paper feeds into the reproducibility crisis. Learn more about writing for reproducibility .

In a study published in The Journal of Obstetrics and Gynecology of India by Dr. Suvarna Satish Khadilkar, she reviewed 400 rejected manuscripts to see why they were rejected. Her studies revealed that poor methodology was a top reason for the submission having a final disposition of rejection.

Aside from publication chances, Dr. Gareth Dyke believes a clear hypothesis helps efficiency.

“Developing a clear and testable hypothesis for your research project means that you will not waste time, energy, and money with your work,” said Dyke. “Refining a hypothesis that is both meaningful, interesting, attainable, and testable is the goal of all effective research.”

Types of research hypotheses

There can be overlap in these types of hypotheses.

Simple hypothesis

A simple hypothesis is a hypothesis at its most basic form. It shows the relationship of one independent and one independent variable.

Example: Drinking soda (independent variable) every day leads to obesity (dependent variable).

Complex hypothesis

A complex hypothesis shows the relationship of two or more independent and dependent variables.

Example: Drinking soda (independent variable) every day leads to obesity (dependent variable) and heart disease (dependent variable).

Directional hypothesis

A directional hypothesis guesses which way the results of an experiment will go. It uses words like increase, decrease, higher, lower, positive, negative, more, or less. It is also frequently used in statistics.

Example: Humans exposed to radiation have a higher risk of cancer than humans not exposed to radiation.

Non-directional hypothesis

A non-directional hypothesis says there will be an effect on the dependent variable, but it does not say which direction.

Associative hypothesis

An associative hypothesis says that when one variable changes, so does the other variable.

Alternative hypothesis

An alternative hypothesis states that the variables have a relationship.

• The opposite of a null hypothesis

Example: An apple a day keeps the doctor away.

Null hypothesis

A null hypothesis states that there is no relationship between the two variables. It is posed as the opposite of what the alternative hypothesis states.

Researchers use a null hypothesis to work to be able to reject it. A null hypothesis:

• Can never be proven
• Can only be rejected
• Is the opposite of an alternative hypothesis

Example: An apple a day does not keep the doctor away.

Logical hypothesis

A logical hypothesis is a suggested explanation while using limited evidence.

Example: Bats can navigate in the dark better than tigers.

In this hypothesis, the researcher knows that tigers cannot see in the dark, and bats mostly live in darkness.

Empirical hypothesis

An empirical hypothesis is also called a “working hypothesis.” It uses the trial and error method and changes around the independent variables.

• An apple a day keeps the doctor away.
• Two apples a day keep the doctor away.
• Three apples a day keep the doctor away.

In this case, the research changes the hypothesis as the researcher learns more about his/her research.

Statistical hypothesis

A statistical hypothesis is a look of a part of a population or statistical model. This type of hypothesis is especially useful if you are making a statement about a large population. Instead of having to test the entire population of Illinois, you could just use a smaller sample of people who live there.

Example: 70% of people who live in Illinois are iron deficient.

Causal hypothesis

A causal hypothesis states that the independent variable will have an effect on the dependent variable.

Example: Using tobacco products causes cancer.

Final thoughts

Make sure your research is error-free before you send it to your preferred journal . Check our our English Editing services to avoid your chances of desk rejection.

Jonny Rhein, BA

See our "Privacy Policy"

• How it works

How to Write a Hypothesis – Steps & Tips

Published by Alaxendra Bets at August 14th, 2021 , Revised On October 26, 2023

What is a Research Hypothesis?

You can test a research statement with the help of experimental or theoretical research, known as a hypothesis.

If you want to find out the similarities, differences, and relationships between variables, you must write a testable hypothesis before compiling the data, performing analysis, and generating results to complete.

The data analysis and findings will help you test the hypothesis and see whether it is true or false. Here is all you need to know about how to write a hypothesis for a  dissertation .

Research Hypothesis Definition

Not sure what the meaning of the research hypothesis is?

A research hypothesis predicts an answer to the research question  based on existing theoretical knowledge or experimental data.

Some studies may have multiple hypothesis statements depending on the research question(s).  A research hypothesis must be based on formulas, facts, and theories. It should be testable by data analysis, observations, experiments, or other scientific methodologies that can refute or support the statement.

Variables in Hypothesis

Developing a hypothesis is easy. Most research studies have two or more variables in the hypothesis, particularly studies involving correlational and experimental research. The researcher can control or change the independent variable(s) while measuring and observing the independent variable(s).

“How long a student sleeps affects test scores.”

In the above statement, the dependent variable is the test score, while the independent variable is the length of time spent in sleep. Developing a hypothesis will be easy if you know your research’s dependent and independent variables.

Once you have developed a thesis statement, questions such as how to write a hypothesis for the dissertation and how to test a research hypothesis become pretty straightforward.

Looking for dissertation help?

Researchprospect to the rescue then.

We have expert writers on our team who are skilled at helping students with quantitative dissertations across a variety of STEM disciplines. Guaranteeing 100% satisfaction!

Step-by-Step Guide on How to Write a Hypothesis

Here are the steps involved in how to write a hypothesis for a dissertation.

Step 1: Start with a Research Question

• Begin by asking a specific question about a topic of interest.
• This question should be clear, concise, and researchable.

Example: Does exposure to sunlight affect plant growth?

Step 2: Do Preliminary Research

• Before formulating a hypothesis, conduct background research to understand existing knowledge on the topic.
• Familiarise yourself with prior studies, theories, or observations related to the research question.

Step 3: Define Variables

• Independent Variable (IV): The factor that you change or manipulate in an experiment.
• Dependent Variable (DV): The factor that you measure.

Example: IV: Amount of sunlight exposure (e.g., 2 hours/day, 4 hours/day, 8 hours/day) DV: Plant growth (e.g., height in centimetres)

Step 4: Formulate the Hypothesis

• A hypothesis is a statement that predicts the relationship between variables.
• It is often written as an “if-then” statement.

Example: If plants receive more sunlight, then they will grow taller.

Step 5: Ensure it is Testable

A good hypothesis is empirically testable. This means you should be able to design an experiment or observation to test its validity.

Example: You can set up an experiment where plants are exposed to varying amounts of sunlight and then measure their growth over a period of time.

Step 6: Consider Potential Confounding Variables

• Confounding variables are factors other than the independent variable that might affect the outcome.
• It is important to identify these to ensure that they do not skew your results.

Example: Soil quality, water frequency, or type of plant can all affect growth. Consider keeping these constant in your experiment.

Step 7: Write the Null Hypothesis

• The null hypothesis is a statement that there is no effect or no relationship between the variables.
• It is what you aim to disprove or reject through your research.

Example: There is no difference in plant growth regardless of the amount of sunlight exposure.

Step 8: Test your Hypothesis

Design an experiment or conduct observations to test your hypothesis.

Example: Grow three sets of plants: one set exposed to 2 hours of sunlight daily, another exposed to 4 hours, and a third exposed to 8 hours. Measure and compare their growth after a set period.

Step 9: Analyse the Results

After testing, review your data to determine if it supports your hypothesis.

Step 10: Draw Conclusions

• Based on your findings, determine whether you can accept or reject the hypothesis.
• Remember, even if you reject your hypothesis, it’s a valuable result. It can guide future research and refine questions.

Three Ways to Phrase a Hypothesis

Try to use “if”… and “then”… to identify the variables. The independent variable should be present in the first part of the hypothesis, while the dependent variable will form the second part of the statement. Consider understanding the below research hypothesis example to create a specific, clear, and concise research hypothesis;

If an obese lady starts attending Zomba fitness classes, her health will improve.

In academic research, you can write the predicted variable relationship directly because most research studies correlate terms.

The number of Zomba fitness classes attended by the obese lady has a positive effect on health.

If your research compares two groups, then you can develop a hypothesis statement on their differences.

An obese lady who attended most Zumba fitness classes will have better health than those who attended a few.

How to Write a Null Hypothesis

If a statistical analysis is involved in your research, then you must create a null hypothesis. If you find any relationship between the variables, then the null hypothesis will be the default position that there is no relationship between them. H0 is the symbol for the null hypothesis, while the hypothesis is represented as H1. The null hypothesis will also answer your question, “How to test the research hypothesis in the dissertation.”

H0: The number of Zumba fitness classes attended by the obese lady does not affect her health.

H1: The number of Zumba fitness classes attended by obese lady positively affects health.

Also see:  Your Dissertation in Education

Hypothesis Examples

Research Question: Does the amount of sunlight a plant receives affect its growth? Hypothesis: Plants that receive more sunlight will grow taller than plants that receive less sunlight.

Research Question: Do students who eat breakfast perform better in school exams than those who don’t? Hypothesis: Students who eat a morning breakfast will score higher on school exams compared to students who skip breakfast.

Research Question: Does listening to music while studying impact a student’s ability to retain information? Hypothesis 1 (Directional): Students who listen to music while studying will retain less information than those who study in silence. Hypothesis 2 (Non-directional): There will be a difference in information retention between students who listen to music while studying and those who study in silence.

How can ResearchProspect Help?

If you are unsure about how to rest a research hypothesis in a dissertation or simply unsure about how to develop a hypothesis for your research, then you can take advantage of our dissertation services which cover every tiny aspect of a dissertation project you might need help with including but not limited to setting up a hypothesis and research questions,  help with individual chapters ,  full dissertation writing ,  statistical analysis , and much more.

Frequently Asked Questions

What are the 5 rules for writing a good hypothesis.

• Clear Statement: State a clear relationship between variables.
• Testable: Ensure it can be investigated and measured.
• Specific: Avoid vague terms, be precise in predictions.
• Falsifiable: Design to allow potential disproof.
• Relevant: Address research question and align with existing knowledge.

What is a hypothesis in simple words?

A hypothesis is an educated guess or prediction about something that can be tested. It is a statement that suggests a possible explanation for an event or phenomenon based on prior knowledge or observation. Scientists use hypotheses as a starting point for experiments to discover if they are true or false.

What is the hypothesis and examples?

A hypothesis is a testable prediction or explanation for an observation or phenomenon. For example, if plants are given sunlight, then they will grow. In this case, the hypothesis suggests that sunlight has a positive effect on plant growth. It can be tested by experimenting with plants in varying light conditions.

What is the hypothesis in research definition?

A hypothesis in research is a clear, testable statement predicting the possible outcome of a study based on prior knowledge and observation. It serves as the foundation for conducting experiments or investigations. Researchers test the validity of the hypothesis to draw conclusions and advance knowledge in a particular field.

Why is it called a hypothesis?

The term “hypothesis” originates from the Greek word “hypothesis,” which means “base” or “foundation.” It’s used to describe a foundational statement or proposition that can be tested. In scientific contexts, it denotes a tentative explanation for a phenomenon, serving as a starting point for investigation or experimentation.

You May Also Like

How to write a hypothesis for dissertation,? A hypothesis is a statement that can be tested with the help of experimental or theoretical research.

Find how to write research questions with the mentioned steps required for a perfect research question. Choose an interesting topic and begin your research.

To help students organise their dissertation proposal paper correctly, we have put together detailed guidelines on how to structure a dissertation proposal.

USEFUL LINKS

LEARNING RESOURCES

COMPANY DETAILS

• How It Works

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.

How to Develop a Good Research Hypothesis

The story of a research study begins by asking a question. Researchers all around the globe are asking curious questions and formulating research hypothesis. However, whether the research study provides an effective conclusion depends on how well one develops a good research hypothesis. Research hypothesis examples could help researchers get an idea as to how to write a good research hypothesis.

This blog will help you understand what is a research hypothesis, its characteristics and, how to formulate a research hypothesis

Table of Contents

What is Hypothesis?

Hypothesis is an assumption or an idea proposed for the sake of argument so that it can be tested. It is a precise, testable statement of what the researchers predict will be outcome of the study.  Hypothesis usually involves proposing a relationship between two variables: the independent variable (what the researchers change) and the dependent variable (what the research measures).

What is a Research Hypothesis?

Research hypothesis is a statement that introduces a research question and proposes an expected result. It is an integral part of the scientific method that forms the basis of scientific experiments. Therefore, you need to be careful and thorough when building your research hypothesis. A minor flaw in the construction of your hypothesis could have an adverse effect on your experiment. In research, there is a convention that the hypothesis is written in two forms, the null hypothesis, and the alternative hypothesis (called the experimental hypothesis when the method of investigation is an experiment).

Characteristics of a Good Research Hypothesis

As the hypothesis is specific, there is a testable prediction about what you expect to happen in a study. You may consider drawing hypothesis from previously published research based on the theory.

A good research hypothesis involves more effort than just a guess. In particular, your hypothesis may begin with a question that could be further explored through background research.

To help you formulate a promising research hypothesis, you should ask yourself the following questions:

• Is the language clear and focused?
• What is the relationship between your hypothesis and your research topic?
• Is your hypothesis testable? If yes, then how?
• What are the possible explanations that you might want to explore?
• Does your hypothesis include both an independent and dependent variable?
• Can you manipulate your variables without hampering the ethical standards?
• Does your research predict the relationship and outcome?
• Is your research simple and concise (avoids wordiness)?
• Is it clear with no ambiguity or assumptions about the readers’ knowledge
• Is your research observable and testable results?
• Is it relevant and specific to the research question or problem?

The questions listed above can be used as a checklist to make sure your hypothesis is based on a solid foundation. Furthermore, it can help you identify weaknesses in your hypothesis and revise it if necessary.

Source: Educational Hub

How to formulate a research hypothesis.

A testable hypothesis is not a simple statement. It is rather an intricate statement that needs to offer a clear introduction to a scientific experiment, its intentions, and the possible outcomes. However, there are some important things to consider when building a compelling hypothesis.

1. State the problem that you are trying to solve.

Make sure that the hypothesis clearly defines the topic and the focus of the experiment.

2. Try to write the hypothesis as an if-then statement.

Follow this template: If a specific action is taken, then a certain outcome is expected.

3. Define the variables

Independent variables are the ones that are manipulated, controlled, or changed. Independent variables are isolated from other factors of the study.

Dependent variables , as the name suggests are dependent on other factors of the study. They are influenced by the change in independent variable.

4. Scrutinize the hypothesis

Evaluate assumptions, predictions, and evidence rigorously to refine your understanding.

Types of Research Hypothesis

The types of research hypothesis are stated below:

1. Simple Hypothesis

It predicts the relationship between a single dependent variable and a single independent variable.

2. Complex Hypothesis

It predicts the relationship between two or more independent and dependent variables.

3. Directional Hypothesis

It specifies the expected direction to be followed to determine the relationship between variables and is derived from theory. Furthermore, it implies the researcher’s intellectual commitment to a particular outcome.

4. Non-directional Hypothesis

It does not predict the exact direction or nature of the relationship between the two variables. The non-directional hypothesis is used when there is no theory involved or when findings contradict previous research.

5. Associative and Causal Hypothesis

The associative hypothesis defines interdependency between variables. A change in one variable results in the change of the other variable. On the other hand, the causal hypothesis proposes an effect on the dependent due to manipulation of the independent variable.

6. Null Hypothesis

Null hypothesis states a negative statement to support the researcher’s findings that there is no relationship between two variables. There will be no changes in the dependent variable due the manipulation of the independent variable. Furthermore, it states results are due to chance and are not significant in terms of supporting the idea being investigated.

7. Alternative Hypothesis

It states that there is a relationship between the two variables of the study and that the results are significant to the research topic. An experimental hypothesis predicts what changes will take place in the dependent variable when the independent variable is manipulated. Also, it states that the results are not due to chance and that they are significant in terms of supporting the theory being investigated.

Research Hypothesis Examples of Independent and Dependent Variables

Research Hypothesis Example 1 The greater number of coal plants in a region (independent variable) increases water pollution (dependent variable). If you change the independent variable (building more coal factories), it will change the dependent variable (amount of water pollution).

Research Hypothesis Example 2 What is the effect of diet or regular soda (independent variable) on blood sugar levels (dependent variable)? If you change the independent variable (the type of soda you consume), it will change the dependent variable (blood sugar levels)

You should not ignore the importance of the above steps. The validity of your experiment and its results rely on a robust testable hypothesis. Developing a strong testable hypothesis has few advantages, it compels us to think intensely and specifically about the outcomes of a study. Consequently, it enables us to understand the implication of the question and the different variables involved in the study. Furthermore, it helps us to make precise predictions based on prior research. Hence, forming a hypothesis would be of great value to the research. Here are some good examples of testable hypotheses.

More importantly, you need to build a robust testable research hypothesis for your scientific experiments. A testable hypothesis is a hypothesis that can be proved or disproved as a result of experimentation.

Importance of a Testable Hypothesis

To devise and perform an experiment using scientific method, you need to make sure that your hypothesis is testable. To be considered testable, some essential criteria must be met:

• There must be a possibility to prove that the hypothesis is true.
• There must be a possibility to prove that the hypothesis is false.
• The results of the hypothesis must be reproducible.

Without these criteria, the hypothesis and the results will be vague. As a result, the experiment will not prove or disprove anything significant.

What are your experiences with building hypotheses for scientific experiments? What challenges did you face? How did you overcome these challenges? Please share your thoughts with us in the comments section.

Frequently Asked Questions

The steps to write a research hypothesis are: 1. Stating the problem: Ensure that the hypothesis defines the research problem 2. Writing a hypothesis as an 'if-then' statement: Include the action and the expected outcome of your study by following a ‘if-then’ structure. 3. Defining the variables: Define the variables as Dependent or Independent based on their dependency to other factors. 4. Scrutinizing the hypothesis: Identify the type of your hypothesis

Hypothesis testing is a statistical tool which is used to make inferences about a population data to draw conclusions for a particular hypothesis.

Hypothesis in statistics is a formal statement about the nature of a population within a structured framework of a statistical model. It is used to test an existing hypothesis by studying a population.

Research hypothesis is a statement that introduces a research question and proposes an expected result. It forms the basis of scientific experiments.

The different types of hypothesis in research are: • Null hypothesis: Null hypothesis is a negative statement to support the researcher’s findings that there is no relationship between two variables. • Alternate hypothesis: Alternate hypothesis predicts the relationship between the two variables of the study. • Directional hypothesis: Directional hypothesis specifies the expected direction to be followed to determine the relationship between variables. • Non-directional hypothesis: Non-directional hypothesis does not predict the exact direction or nature of the relationship between the two variables. • Simple hypothesis: Simple hypothesis predicts the relationship between a single dependent variable and a single independent variable. • Complex hypothesis: Complex hypothesis predicts the relationship between two or more independent and dependent variables. • Associative and casual hypothesis: Associative and casual hypothesis predicts the relationship between two or more independent and dependent variables. • Empirical hypothesis: Empirical hypothesis can be tested via experiments and observation. • Statistical hypothesis: A statistical hypothesis utilizes statistical models to draw conclusions about broader populations.

Wow! You really simplified your explanation that even dummies would find it easy to comprehend. Thank you so much.

Thanks a lot for your valuable guidance.

I enjoy reading the post. Hypotheses are actually an intrinsic part in a study. It bridges the research question and the methodology of the study.

Useful piece!

This is awesome.Wow.

It very interesting to read the topic, can you guide me any specific example of hypothesis process establish throw the Demand and supply of the specific product in market

Nicely explained

It is really a useful for me Kindly give some examples of hypothesis

It was a well explained content ,can you please give me an example with the null and alternative hypothesis illustrated

clear and concise. thanks.

So Good so Amazing

Good to learn

Thanks a lot for explaining to my level of understanding

Explained well and in simple terms. Quick read! Thank you

It awesome. It has really positioned me in my research project

Rate this article Cancel Reply

Your email address will not be published.

Enago Academy's Most Popular Articles

• Reporting Research

Choosing the Right Analytical Approach: Thematic analysis vs. content analysis for data interpretation

In research, choosing the right approach to understand data is crucial for deriving meaningful insights.…

Comparing Cross Sectional and Longitudinal Studies: 5 steps for choosing the right approach

The process of choosing the right research design can put ourselves at the crossroads of…

• Industry News

COPE Forum Discussion Highlights Challenges and Urges Clarity in Institutional Authorship Standards

The COPE forum discussion held in December 2023 initiated with a fundamental question — is…

• Career Corner

Unlocking the Power of Networking in Academic Conferences

Embarking on your first academic conference experience? Fear not, we got you covered! Academic conferences…

Research Recommendations – Guiding policy-makers for evidence-based decision making

Research recommendations play a crucial role in guiding scholars and researchers toward fruitful avenues of…

Choosing the Right Analytical Approach: Thematic analysis vs. content analysis for…

Comparing Cross Sectional and Longitudinal Studies: 5 steps for choosing the right…

How to Design Effective Research Questionnaires for Robust Findings

Sign-up to read more

Subscribe for free to get unrestricted access to all our resources on research writing and academic publishing including:

• 2000+ blog articles
• 50+ Webinars
• 10+ Expert podcasts
• 50+ Infographics
• 10+ Checklists
• Research Guides

We hate spam too. We promise to protect your privacy and never spam you.

I am looking for Editing/ Proofreading services for my manuscript Tentative date of next journal submission:

What should universities' stance be on AI tools in research and academic writing?

Research Methods in Dentistry pp 87–114 Cite as

Writing a Research Proposal

• Fahimeh Tabatabaei 3 &
• Lobat Tayebi 3  
• First Online: 10 April 2022

808 Accesses

A research proposal is a roadmap that brings the researcher closer to the objectives, takes the research topic from a purely subjective mind, and manifests an objective plan. It shows us what steps we need to take to reach the objective, what questions we should answer, and how much time we need. It is a framework based on which you can perform your research in a well-organized and timely manner. In other words, by writing a research proposal, you get a map that shows the direction to the destination (answering the research question). If the proposal is poorly prepared, after spending a lot of energy and money, you may realize that the result of the research has nothing to do with the initial objective, and the study may end up nowhere. Therefore, writing the proposal shows that the researcher is aware of the proper research and can justify the significance of his/her idea.

This is a preview of subscription content, log in via an institution .

Buying options

• Available as PDF
• Read on any device
• Instant download
• Own it forever
• Available as EPUB and PDF
• Compact, lightweight edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info
• Durable hardcover edition

Tax calculation will be finalised at checkout

Purchases are for personal use only

A. Gholipour, E.Y. Lee, S.K. Warfield, The anatomy and art of writing a successful grant application: A practical step-by-step approach. Pediatr. Radiol. 44 (12), 1512–1517 (2014)

Article   Google Scholar  

L.S. Marshall, Research commentary: Grant writing: Part I first things first …. J. Radiol. Nurs. 31 (4), 154–155 (2012)

E.K. Proctor, B.J. Powell, A.A. Baumann, A.M. Hamilton, R.L. Santens, Writing implementation research grant proposals: Ten key ingredients. Implement. Sci. 7 (1), 96 (2012)

K.C. Chung, M.J. Shauver, Fundamental principles of writing a successful grant proposal. J. Hand Surg. Am. 33 (4), 566–572 (2008)

A.A. Monte, A.M. Libby, Introduction to the specific aims page of a grant proposal. Kline JA, editor. Acad. Emerg. Med. 25 (9), 1042–1047 (2018)

P. Kan, M.R. Levitt, W.J. Mack, R.M. Starke, K.N. Sheth, F.C. Albuquerque, et al., National Institutes of Health grant opportunities for the neurointerventionalist: Preparation and choosing the right mechanism. J. Neurointerv. Surg. 13 (3), 287–289 (2021)

A.M. Goldstein, S. Balaji, A.A. Ghaferi, A. Gosain, M. Maggard-Gibbons, B. Zuckerbraun, et al., An algorithmic approach to an impactful specific aims page. Surgery 169 (4), 816–820 (2021)

S. Engberg, D.Z. Bliss, Writing a grant proposal—Part 1. J. Wound Ostomy Cont. Nurs. 32 (3), 157–162 (2005)

D.Z. Bliss, K. Savik, Writing a grant proposal—Part 2. J. Wound Ostomy Cont. Nurs. 32 (4), 226–229 (2005)

D.Z. Bliss, Writing a grant proposal—Part 6. J. Wound Ostomy Cont. Nurs. 32 (6), 365–367 (2005)

J.C. Liu, M.A. Pynnonen, M. St John, E.L. Rosenthal, M.E. Couch, C.E. Schmalbach, Grant-writing pearls and pitfalls. Otolaryngol. Neck. Surg. 154 (2), 226–232 (2016)

R.J. Santen, E.J. Barrett, H.M. Siragy, L.S. Farhi, L. Fishbein, R.M. Carey, The jewel in the crown: Specific aims section of investigator-initiated grant proposals. J. Endocr. Soc. 1 (9), 1194–1202 (2017)

O.J. Arthurs, Think it through first: Questions to consider in writing a successful grant application. Pediatr. Radiol. 44 (12), 1507–1511 (2014)

M. Monavarian, Basics of scientific and technical writing. MRS Bull. 46 (3), 284–286 (2021)

Additional Resources

https://grants.nih.gov

https://grants.nih.gov/grants/oer.htm

https://www.ninr.nih.gov

https://www.niaid.nih.gov

http://www.grantcentral.com

http://www.saem.org/research

http://www.cfda.gov

http://www.ahrq.gov

http://www.nsf/gov

Download references

Author information

Authors and affiliations.

School of Dentistry, Marquette University, Milwaukee, WI, USA

Fahimeh Tabatabaei & Lobat Tayebi

You can also search for this author in PubMed   Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this chapter

Cite this chapter.

Tabatabaei, F., Tayebi, L. (2022). Writing a Research Proposal. In: Research Methods in Dentistry. Springer, Cham. https://doi.org/10.1007/978-3-030-98028-3_4

Download citation

DOI : https://doi.org/10.1007/978-3-030-98028-3_4

Published : 10 April 2022

Publisher Name : Springer, Cham

Print ISBN : 978-3-030-98027-6

Online ISBN : 978-3-030-98028-3

eBook Packages : Engineering Engineering (R0)

Share this chapter

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

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

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research

What (Exactly) Is A Research Proposal?

A simple explainer with examples + free template.

By: Derek Jansen (MBA) | Reviewed By: Dr Eunice Rautenbach | June 2020 (Updated April 2023)

Whether you’re nearing the end of your degree and your dissertation is on the horizon, or you’re planning to apply for a PhD program, chances are you’ll need to craft a convincing research proposal . If you’re on this page, you’re probably unsure exactly what the research proposal is all about. Well, you’ve come to the right place.

Overview: Research Proposal Basics

• What a research proposal is
• What a research proposal needs to cover
• How to structure your research proposal
• Example /sample proposals
• Proposal writing FAQs
• Key takeaways & additional resources

What is a research proposal?

Simply put, a research proposal is a structured, formal document that explains what you plan to research (your research topic), why it’s worth researching (your justification), and how  you plan to investigate it (your methodology). 

The purpose of the research proposal (its job, so to speak) is to convince  your research supervisor, committee or university that your research is  suitable  (for the requirements of the degree program) and  manageable  (given the time and resource constraints you will face). 

The most important word here is “ convince ” – in other words, your research proposal needs to  sell  your research idea (to whoever is going to approve it). If it doesn’t convince them (of its suitability and manageability), you’ll need to revise and resubmit . This will cost you valuable time, which will either delay the start of your research or eat into its time allowance (which is bad news). 

What goes into a research proposal?

A good dissertation or thesis proposal needs to cover the “ what “, “ why ” and” how ” of the proposed study. Let’s look at each of these attributes in a little more detail:

Your proposal needs to clearly articulate your research topic . This needs to be specific and unambiguous . Your research topic should make it clear exactly what you plan to research and in what context. Here’s an example of a well-articulated research topic:

An investigation into the factors which impact female Generation Y consumer’s likelihood to promote a specific makeup brand to their peers: a British context

As you can see, this topic is extremely clear. From this one line we can see exactly:

• What’s being investigated – factors that make people promote or advocate for a brand of a specific makeup brand
• Who it involves – female Gen-Y consumers
• In what context – the United Kingdom

So, make sure that your research proposal provides a detailed explanation of your research topic . If possible, also briefly outline your research aims and objectives , and perhaps even your research questions (although in some cases you’ll only develop these at a later stage). Needless to say, don’t start writing your proposal until you have a clear topic in mind , or you’ll end up waffling and your research proposal will suffer as a result of this.

Need a helping hand?

As we touched on earlier, it’s not good enough to simply propose a research topic – you need to justify why your topic is original . In other words, what makes it  unique ? What gap in the current literature does it fill? If it’s simply a rehash of the existing research, it’s probably not going to get approval – it needs to be fresh.

But,  originality  alone is not enough. Once you’ve ticked that box, you also need to justify why your proposed topic is  important . In other words, what value will it add to the world if you achieve your research aims?

As an example, let’s look at the sample research topic we mentioned earlier (factors impacting brand advocacy). In this case, if the research could uncover relevant factors, these findings would be very useful to marketers in the cosmetics industry, and would, therefore, have commercial value . That is a clear justification for the research.

So, when you’re crafting your research proposal, remember that it’s not enough for a topic to simply be unique. It needs to be useful and value-creating – and you need to convey that value in your proposal. If you’re struggling to find a research topic that makes the cut, watch  our video covering how to find a research topic .

It’s all good and well to have a great topic that’s original and valuable, but you’re not going to convince anyone to approve it without discussing the practicalities – in other words:

• How will you actually undertake your research (i.e., your methodology)?
• Is your research methodology appropriate given your research aims?
• Is your approach manageable given your constraints (time, money, etc.)?

While it’s generally not expected that you’ll have a fully fleshed-out methodology at the proposal stage, you’ll likely still need to provide a high-level overview of your research methodology . Here are some important questions you’ll need to address in your research proposal:

• Will you take a qualitative , quantitative or mixed -method approach?
• What sampling strategy will you adopt?
• How will you collect your data (e.g., interviews, surveys, etc)?
• How will you analyse your data (e.g., descriptive and inferential statistics , content analysis, discourse analysis, etc, .)?
• What potential limitations will your methodology carry?

So, be sure to give some thought to the practicalities of your research and have at least a basic methodological plan before you start writing up your proposal. If this all sounds rather intimidating, the video below provides a good introduction to research methodology and the key choices you’ll need to make.

How To Structure A Research Proposal

Now that we’ve covered the key points that need to be addressed in a proposal, you may be wondering, “ But how is a research proposal structured? “.

While the exact structure and format required for a research proposal differs from university to university, there are four “essential ingredients” that commonly make up the structure of a research proposal:

• A rich introduction and background to the proposed research
• An initial literature review covering the existing research
• An overview of the proposed research methodology
• A discussion regarding the practicalities (project plans, timelines, etc.)

In the video below, we unpack each of these four sections, step by step.

Research Proposal Examples/Samples

In the video below, we provide a detailed walkthrough of two successful research proposals (Master’s and PhD-level), as well as our popular free proposal template.

Proposal Writing FAQs

How long should a research proposal be.

This varies tremendously, depending on the university, the field of study (e.g., social sciences vs natural sciences), and the level of the degree (e.g. undergraduate, Masters or PhD) – so it’s always best to check with your university what their specific requirements are before you start planning your proposal.

As a rough guide, a formal research proposal at Masters-level often ranges between 2000-3000 words, while a PhD-level proposal can be far more detailed, ranging from 5000-8000 words. In some cases, a rough outline of the topic is all that’s needed, while in other cases, universities expect a very detailed proposal that essentially forms the first three chapters of the dissertation or thesis.

The takeaway – be sure to check with your institution before you start writing.

How do I choose a topic for my research proposal?

Finding a good research topic is a process that involves multiple steps. We cover the topic ideation process in this video post.

How do I write a literature review for my proposal?

While you typically won’t need a comprehensive literature review at the proposal stage, you still need to demonstrate that you’re familiar with the key literature and are able to synthesise it. We explain the literature review process here.

How do I create a timeline and budget for my proposal?

We explain how to craft a project plan/timeline and budget in Research Proposal Bootcamp .

Which referencing format should I use in my research proposal?

The expectations and requirements regarding formatting and referencing vary from institution to institution. Therefore, you’ll need to check this information with your university.

What common proposal writing mistakes do I need to look out for?

We’ve create a video post about some of the most common mistakes students make when writing a proposal – you can access that here . If you’re short on time, here’s a quick summary:

• The research topic is too broad (or just poorly articulated).
• The research aims, objectives and questions don’t align.
• The research topic is not well justified.
• The study has a weak theoretical foundation.
• The research design is not well articulated well enough.
• Poor writing and sloppy presentation.
• Poor project planning and risk management.
• Not following the university’s specific criteria.

Key Takeaways & Additional Resources

As you write up your research proposal, remember the all-important core purpose:  to convince . Your research proposal needs to sell your study in terms of suitability and viability. So, focus on crafting a convincing narrative to ensure a strong proposal.

At the same time, pay close attention to your university’s requirements. While we’ve covered the essentials here, every institution has its own set of expectations and it’s essential that you follow these to maximise your chances of approval.

By the way, we’ve got plenty more resources to help you fast-track your research proposal. Here are some of our most popular resources to get you started:

• Proposal Writing 101 : A Introductory Webinar
• Research Proposal Bootcamp : The Ultimate Online Course
• Template : A basic template to help you craft your proposal

If you’re looking for 1-on-1 support with your research proposal, be sure to check out our private coaching service , where we hold your hand through the proposal development process (and the entire research journey), step by step.

Psst… there’s more!

This post is an extract from our bestselling Udemy Course, Research Proposal Bootcamp . If you want to work smart, you don't want to miss this .

You Might Also Like:

51 Comments

I truly enjoyed this video, as it was eye-opening to what I have to do in the preparation of preparing a Research proposal.

I would be interested in getting some coaching.

I real appreciate on your elaboration on how to develop research proposal,the video explains each steps clearly.

Thank you for the video. It really assisted me and my niece. I am a PhD candidate and she is an undergraduate student. It is at times, very difficult to guide a family member but with this video, my job is done.

In view of the above, I welcome more coaching.

Wonderful guidelines, thanks

This is very helpful. Would love to continue even as I prepare for starting my masters next year.

Thanks for the work done, the text was helpful to me

Bundle of thanks to you for the research proposal guide it was really good and useful if it is possible please send me the sample of research proposal

You’re most welcome. We don’t have any research proposals that we can share (the students own the intellectual property), but you might find our research proposal template useful: https://gradcoach.com/research-proposal-template/

Cheruiyot Moses Kipyegon

Thanks alot. It was an eye opener that came timely enough before my imminent proposal defense. Thanks, again

thank you very much your lesson is very interested may God be with you

I am an undergraduate student (First Degree) preparing to write my project,this video and explanation had shed more light to me thanks for your efforts keep it up.

Very useful. I am grateful.

this is a very a good guidance on research proposal, for sure i have learnt something

Wonderful guidelines for writing a research proposal, I am a student of m.phil( education), this guideline is suitable for me. Thanks

You’re welcome 🙂

Thank you, this was so helpful.

A really great and insightful video. It opened my eyes as to how to write a research paper. I would like to receive more guidance for writing my research paper from your esteemed faculty.

Thank you, great insights

Thank you, great insights, thank you so much, feeling edified

Wow thank you, great insights, thanks a lot

Thank you. This is a great insight. I am a student preparing for a PhD program. I am requested to write my Research Proposal as part of what I am required to submit before my unconditional admission. I am grateful having listened to this video which will go a long way in helping me to actually choose a topic of interest and not just any topic as well as to narrow down the topic and be specific about it. I indeed need more of this especially as am trying to choose a topic suitable for a DBA am about embarking on. Thank you once more. The video is indeed helpful.

Have learnt a lot just at the right time. Thank you so much.

thank you very much ,because have learn a lot things concerning research proposal and be blessed u for your time that you providing to help us

Hi. For my MSc medical education research, please evaluate this topic for me: Training Needs Assessment of Faculty in Medical Training Institutions in Kericho and Bomet Counties

I have really learnt a lot based on research proposal and it’s formulation

Thank you. I learn much from the proposal since it is applied

Your effort is much appreciated – you have good articulation.

You have good articulation.

I do applaud your simplified method of explaining the subject matter, which indeed has broaden my understanding of the subject matter. Definitely this would enable me writing a sellable research proposal.

This really helping

Great! I liked your tutoring on how to find a research topic and how to write a research proposal. Precise and concise. Thank you very much. Will certainly share this with my students. Research made simple indeed.

Thank you very much. I an now assist my students effectively.

Thank you very much. I can now assist my students effectively.

I need any research proposal

Thank you for these videos. I will need chapter by chapter assistance in writing my MSc dissertation

Very helpfull

the videos are very good and straight forward

thanks so much for this wonderful presentations, i really enjoyed it to the fullest wish to learn more from you

Thank you very much. I learned a lot from your lecture.

I really enjoy the in-depth knowledge on research proposal you have given. me. You have indeed broaden my understanding and skills. Thank you

interesting session this has equipped me with knowledge as i head for exams in an hour’s time, am sure i get A++

This article was most informative and easy to understand. I now have a good idea of how to write my research proposal.

Thank you very much.

Wow, this literature is very resourceful and interesting to read. I enjoyed it and I intend reading it every now then.

Thank you for the clarity

Thank you. Very helpful.

Thank you very much for this essential piece. I need 1o1 coaching, unfortunately, your service is not available in my country. Anyways, a very important eye-opener. I really enjoyed it. A thumb up to Gradcoach

What is JAM? Please explain.

Thank you so much for these videos. They are extremely helpful! God bless!

very very wonderful…

thank you for the video but i need a written example

Submit a Comment Cancel reply

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

Save my name, email, and website in this browser for the next time I comment.

• Print Friendly

Writing a Research Proposal

Parts of a research proposal, prosana model, introduction, research question, methodology.

• Structure of a Research Proposal
• Common Proposal Writing Mistakes
• Proposal Writing Resources

A research proposal's purpose is to capture the evaluator's attention, demonstrate the study's potential benefits, and prove that it is a logical and consistent approach (Van Ekelenburg, 2010).  To ensure that your research proposal contains these elements, there are several aspects to include in your proposal (Al-Riyami, 2008):

• Objective(s)
• Variables (independent and dependent)
• Research Question and/or hypothesis

Details about what to include in each element are included in the boxes below.  Depending on the topic of your study, some parts may not apply to your proposal.  You can also watch the video below for a brief overview about writing a successful research proposal.

Van Ekelenburg (2010) uses the PROSANA Model to guide researchers in developing rationale and justification for their research projects.  It is an acronym that connects the problem, solution, and benefits of a particular research project.  It is an easy way to remember the critical parts of a research proposal and how they relate to one another.  It includes the following letters (Van Ekelenburg, 2010):

• Problem: Describing the main problem that the researcher is trying to solve.
• Root causes: Describing what is causing the problem.  Why is the topic an issue?
• fOcus: Narrowing down one of the underlying causes on which the researcher will focus for their research project.
• Solutions: Listing potential solutions or approaches to fix to the problem.  There could be more than one.
• Approach: Selecting the solution that the researcher will want to focus on.
• Novelty: Describing how the solution will address or solve the problem.
• Arguments: Explaining how the proposed solution will benefit the problem.

Research proposal titles should be concise and to the point, but informative.  The title of your proposal may be different from the title of your final research project, but that is completely normal!  Your findings may help you come up with a title that is more fitting for the final project.  Characteristics of good proposal titles are (Al-Riyami, 2008):

• Catchy: It catches the reader's attention by peaking their interest.
• Positive: It spins your project in a positive way towards the reader.
• Transparent: It identifies the independent and dependent variables.

It is also common for proposal titles to be very similar to your research question, hypothesis, or thesis statement (Locke et al., 2007).

An abstract is a brief summary (about 300 words) of the study you are proposing.  It includes the following elements (Al-Riyami, 2008):

• Your primary research question(s).
• Hypothesis or main argument.
• Method you will use to complete the study.  This may include the design, sample population, or measuring instruments that you plan to use.

Our guide on writing summaries may help you with this step.

• Writing a Summary by Luann Edwards Last Updated May 22, 2023 1119 views this year

The purpose of the introduction is to give readers background information about your topic.  it gives the readers a basic understanding of your topic so that they can further understand the significance of your proposal.  A good introduction will explain (Al-Riyami, 2008):

• How it relates to other research done on the topic
• Why your research is significant to the field
• The relevance of your study

Your research objectives are the desired outcomes that you will achieve from the research project.  Depending on your research design, these may be generic or very specific.  You may also have more than one objective (Al-Riyami, 2008).

• General objectives are what the research project will accomplish
• Specific objectives relate to the research questions that the researcher aims to answer through the study.

Be careful not to have too many objectives in your proposal, as having too many can make your project lose focus.  Plus, it may not be possible to achieve several objectives in one study.

This section describes the different types of variables that you plan to have in your study and how you will measure them.  According to Al-Riyami (2008), there are four types of research variables:

• Independent:  The person, object, or idea that is manipulated by the researcher.
• Dependent:  The person, object, or idea whose changes are dependent upon the independent variable.  Typically, it is the item that the researcher is measuring for the study.
• Confounding/Intervening:  Factors that may influence the effect of the independent variable on the dependent variable.  These include physical and mental barriers.  Not every study will have intervening variables, but they should be studied if applicable.
• Background:   Factors that are relevant to the study's data and how it can be generalized.  Examples include demographic information such as age, sex, and ethnicity.

Your research proposal should describe each of your variables and how they relate to one another.  Depending on your study, you may not have all four types of variables present.  However, there will always be an independent and dependent variable.

A research question is the main piece of your research project because it explains what your study will discover to the reader.  It is the question that fuels the study, so it is important for it to be precise and unique.  You do not want it to be too broad, and it should identify a relationship between two variables (an independent and a dependent) (Al-Riyami, 2008).  There are six types of research questions (Academic Writer, n.d.):

• Example: "Do people get nervous before speaking in front of an audience?"
• Example: "What are the study habits of college freshmen at Tiffin University?"
• Example: "What primary traits create a successful romantic relationship?"
• Example: "Is there a relationship between a child's performance in school and their parents' socioeconomic status?"
• Example: "Are high school seniors more motivated than high school freshmen?"
• Example: "Do news media outlets impact a person's political opinions?"

For more information on the different types of research questions, you can view the "Research Questions and Hypotheses" tutorial on Academic Writer, located below.  If you are unfamiliar with Academic Writer, we also have a tutorial on using the database located below.

Compose papers in pre-formatted APA templates. Manage references in forms that help craft APA citations. Learn the rules of APA style through tutorials and practice quizzes.

Academic Writer will continue to use the 6th edition guidelines until August 2020. A preview of the 7th edition is available in the footer of the resource's site. Previously known as APA Style Central.

• Academic Writer Tutorial by Pfeiffer Library Last Updated May 22, 2023 15600 views this year

If you know enough about your research topic that you believe a particular outcome may occur as a result of the study, you can include a hypothesis (thesis statement) in your proposal.  A hypothesis is a prediction that you believe will be the outcome of your study.  It explains what you think the relationship will be between the independent and dependent variable (Al-Riyami, 2008).  It is ok if the hypothesis in your proposal turns out to be incorrect, because it is only a prediction!  If you are writing a proposal in the humanities, you may be writing a thesis statement instead of a hypothesis.  A thesis presents the main argument of your research project and leads to corresponding evidence to support your argument.

Hypotheses vs. Theories

Hypotheses are different from theories in that theories represent general principles and sets of rules that explain different phenomena.  They typically represent large areas of study because they are applicable to anything in a particular field.  Hypotheses focus on specific areas within a field and are educated guesses, meaning that they have the potential to be proven wrong (Academic Writer, n.d.).  Because of this, hypotheses can also be formed from theories.

For more information on writing effective thesis statements, you can view our guide on writing thesis statements below.

• Writing Effective Thesis Statements by Luann Edwards Last Updated May 23, 2023 226 views this year

In a research proposal, you must thoroughly explain how you will conduct your study.  This includes things such as (Al-Riyami, 2008):

• Research design:  What research approach will your study take?  Will it be quantitative or qualitative?
• Research subjects/participants:  Who will be participating in your study?  Does your study require human participants?  How will you determine who to study?
• Sample size:  How many participants will your study require?  If you are not using human participants, how much of the sample will you be studying?
• Timeline:  A proposed list of the general tasks and events that you plan to complete the study.  This will include a time frame for each task/event and the order in which they will be completed.
• Interventions:  If you plan on using anything on human participants for the study, you must include information it here.  This is especially important if you plan on using any substances on human subjects.
• Ethical issues:  Are there any potential ethical issues surrounding this study?
• Potential limitations:  Are there any limitations that could skew the data and findings from your study?
• Appendixes:  If you need to present any consent forms, interview questions, surveys, questionnaires, or other items that will be used in your study, you should include samples of each item with an appendix to reference them.  If you are using a copyrighted document, you may need written permission from the original creator to use it in your study.  A copy of the written permission should be included in your proposal.
• Setting:  Where will you be conducting the study?
• Study instruments:  What measuring tools or computer software will you be using to collect data?  How will you collect the data?
• How you will analyze the data:  What strategies or tools will you use to analyze the data you collect?
• Quality control:  Will you have precautions in place to ensure that the study is conducted consistently and that outside factors will not skew the data?
• Budget:  What type of funding will you need for your study?  This will include the funds needed to afford measuring tools, software, etc.
• How you will share the study's findings:  What will you plan to do with the findings?
• Significance of the study: How will your study expand on existing knowledge of the subject area?

For more information on research methodologies, you can view our guide on research methods and methodologies below.

• Research Methodologies by Pfeiffer Library Last Updated Aug 2, 2022 15725 views this year
• << Previous: Welcome
• Next: Structure of a Research Proposal >>
• Last Updated: May 22, 2023 10:46 AM
• URL: https://library.tiffin.edu/writingaresearchproposal

• Privacy Policy

Buy Me a Coffee

Home » How To Write A Research Proposal – Step-by-Step [Template]

How To Write A Research Proposal – Step-by-Step [Template]

Table of Contents

How To Write a Research Proposal

Writing a Research proposal involves several steps to ensure a well-structured and comprehensive document. Here is an explanation of each step:

1. Title and Abstract

• Choose a concise and descriptive title that reflects the essence of your research.
• Write an abstract summarizing your research question, objectives, methodology, and expected outcomes. It should provide a brief overview of your proposal.

2. Introduction:

• Provide an introduction to your research topic, highlighting its significance and relevance.
• Clearly state the research problem or question you aim to address.
• Discuss the background and context of the study, including previous research in the field.

3. Research Objectives

• Outline the specific objectives or aims of your research. These objectives should be clear, achievable, and aligned with the research problem.

4. Literature Review:

• Conduct a comprehensive review of relevant literature and studies related to your research topic.
• Summarize key findings, identify gaps, and highlight how your research will contribute to the existing knowledge.

5. Methodology:

• Describe the research design and methodology you plan to employ to address your research objectives.
• Explain the data collection methods, instruments, and analysis techniques you will use.
• Justify why the chosen methods are appropriate and suitable for your research.

6. Timeline:

• Create a timeline or schedule that outlines the major milestones and activities of your research project.
• Break down the research process into smaller tasks and estimate the time required for each task.

7. Resources:

• Identify the resources needed for your research, such as access to specific databases, equipment, or funding.
• Explain how you will acquire or utilize these resources to carry out your research effectively.

8. Ethical Considerations:

• Discuss any ethical issues that may arise during your research and explain how you plan to address them.
• If your research involves human subjects, explain how you will ensure their informed consent and privacy.

9. Expected Outcomes and Significance:

• Clearly state the expected outcomes or results of your research.
• Highlight the potential impact and significance of your research in advancing knowledge or addressing practical issues.

10. References:

• Provide a list of all the references cited in your proposal, following a consistent citation style (e.g., APA, MLA).

11. Appendices:

• Include any additional supporting materials, such as survey questionnaires, interview guides, or data analysis plans.

Research Proposal Format

The format of a research proposal may vary depending on the specific requirements of the institution or funding agency. However, the following is a commonly used format for a research proposal:

1. Title Page:

• Include the title of your research proposal, your name, your affiliation or institution, and the date.

2. Abstract:

• Provide a brief summary of your research proposal, highlighting the research problem, objectives, methodology, and expected outcomes.

3. Introduction:

• Introduce the research topic and provide background information.
• State the research problem or question you aim to address.
• Explain the significance and relevance of the research.
• Review relevant literature and studies related to your research topic.
• Summarize key findings and identify gaps in the existing knowledge.
• Explain how your research will contribute to filling those gaps.

5. Research Objectives:

• Clearly state the specific objectives or aims of your research.
• Ensure that the objectives are clear, focused, and aligned with the research problem.

6. Methodology:

• Describe the research design and methodology you plan to use.
• Explain the data collection methods, instruments, and analysis techniques.
• Justify why the chosen methods are appropriate for your research.

7. Timeline:

8. Resources:

• Explain how you will acquire or utilize these resources effectively.

9. Ethical Considerations:

• If applicable, explain how you will ensure informed consent and protect the privacy of research participants.

10. Expected Outcomes and Significance:

11. References:

12. Appendices:

Research Proposal Template

Here’s a template for a research proposal:

1. Introduction:

2. Literature Review:

3. Research Objectives:

4. Methodology:

5. Timeline:

6. Resources:

7. Ethical Considerations:

8. Expected Outcomes and Significance:

9. References:

10. Appendices:

Research Proposal Sample

Title: The Impact of Online Education on Student Learning Outcomes: A Comparative Study

1. Introduction

Online education has gained significant prominence in recent years, especially due to the COVID-19 pandemic. This research proposal aims to investigate the impact of online education on student learning outcomes by comparing them with traditional face-to-face instruction. The study will explore various aspects of online education, such as instructional methods, student engagement, and academic performance, to provide insights into the effectiveness of online learning.

2. Objectives

The main objectives of this research are as follows:

• To compare student learning outcomes between online and traditional face-to-face education.
• To examine the factors influencing student engagement in online learning environments.
• To assess the effectiveness of different instructional methods employed in online education.
• To identify challenges and opportunities associated with online education and suggest recommendations for improvement.

3. Methodology

3.1 Study Design

This research will utilize a mixed-methods approach to gather both quantitative and qualitative data. The study will include the following components:

3.2 Participants

The research will involve undergraduate students from two universities, one offering online education and the other providing face-to-face instruction. A total of 500 students (250 from each university) will be selected randomly to participate in the study.

3.3 Data Collection

The research will employ the following data collection methods:

• Quantitative: Pre- and post-assessments will be conducted to measure students’ learning outcomes. Data on student demographics and academic performance will also be collected from university records.
• Qualitative: Focus group discussions and individual interviews will be conducted with students to gather their perceptions and experiences regarding online education.

3.4 Data Analysis

Quantitative data will be analyzed using statistical software, employing descriptive statistics, t-tests, and regression analysis. Qualitative data will be transcribed, coded, and analyzed thematically to identify recurring patterns and themes.

4. Ethical Considerations

The study will adhere to ethical guidelines, ensuring the privacy and confidentiality of participants. Informed consent will be obtained, and participants will have the right to withdraw from the study at any time.

5. Significance and Expected Outcomes

This research will contribute to the existing literature by providing empirical evidence on the impact of online education on student learning outcomes. The findings will help educational institutions and policymakers make informed decisions about incorporating online learning methods and improving the quality of online education. Moreover, the study will identify potential challenges and opportunities related to online education and offer recommendations for enhancing student engagement and overall learning outcomes.

6. Timeline

The proposed research will be conducted over a period of 12 months, including data collection, analysis, and report writing.

The estimated budget for this research includes expenses related to data collection, software licenses, participant compensation, and research assistance. A detailed budget breakdown will be provided in the final research plan.

8. Conclusion

This research proposal aims to investigate the impact of online education on student learning outcomes through a comparative study with traditional face-to-face instruction. By exploring various dimensions of online education, this research will provide valuable insights into the effectiveness and challenges associated with online learning. The findings will contribute to the ongoing discourse on educational practices and help shape future strategies for maximizing student learning outcomes in online education settings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

You may also like

How To Write A Proposal – Step By Step Guide...

Grant Proposal – Example, Template and Guide

How To Write A Business Proposal – Step-by-Step...

Business Proposal – Templates, Examples and Guide

Proposal – Types, Examples, and Writing Guide

How to choose an Appropriate Method for Research?

Mobile Menu Overlay

The White House 1600 Pennsylvania Ave NW Washington, DC 20500

The Economics of Administration Action on Student   Debt

Higher education financing allows many Americans from lower- and middle-income backgrounds to invest in education. However, over the past 30 years, college tuition prices have increased faster than median incomes, leaving many Americans with large amounts of student debt that they struggle or are unable to, pay off. 

Recognizing the burden of this debt, the Biden-Harris Administration has pursued two key strategies for debt reduction and cancellation. The first, student debt relief (SDR), aims to address the ill effects of flaws in the student debt system for borrowers. The second, the SAVE plan, reforms the federal student loan system, improving student loan affordability for future students and providing current graduates with breathing room during the beginning of a new career.

This issue brief examines the factors that precipitated the current student debt landscape, and details how both SDR and SAVE will enhance the economic status of millions of Americans with student debt: enabling them to allocate more funds towards basic necessities, take career risks, start businesses, and purchase homes. This brief highlights credible research, underscoring how the Administration’s student debt relief could boost consumption in the short-term by billions of dollars and could have important impacts on borrower mental health, financial security, and outcomes such as homeownership and entrepreneurship. This brief also details how the SAVE plan makes repaying college costs more affordable for current borrowers and future generations. CEA simulations show that, under SAVE, an average borrower with a bachelor’s degree could save $20,000 in loan payments, while a borrower with an associate degree could see nearly 90 percent savings compared to the standard loan repayment plan. These changes enable more people to pursue education and contribute to the broader economy.

Why do borrowers need relief?

Over the last 20 years especially, the sticker price of college has risen significantly. Despite recent minor declines, sticker prices at public universities (which over 70% of undergraduate students in the United States attend) are 56% higher today than two decades ago. [1] While there are many reasons for this trend, the most rapid increases in tuition often occur during economic downturns as tuitions grow to fill the budgetary holes that are left when states cut their support to public colleges ( Webber, 2017 ; Deming and Walters 2018 ). This is especially problematic given many people choose to return to school during economic downturns ( Betts and MacFarland 1995 ; Hillman and Orians 2013 ). Unfortunately, contracting state appropriations have played a role in shifting the responsibility of financing away from public subsidies and toward students and families ( Turner and Barr, 2013 ; Bound et al., 2019 )–leading many students to take on more debt.

At the same time that college sticker prices have risen, the wage premium (the earnings difference between college goers and high school graduates) has not seen analogous growth. While obtaining a college degree remains a reliable entry point to the middle class, the relative earning gains for degree holders began to stagnate in the early 2000s after increasing for several decades. As shown in Figure 1b, since 2000, the wage premium for both bachelor’s degree holders and those with “some college” education (which includes anyone who enrolled in college but didn’t earn a BA) saw declines around the 2001-02 and 2008-10 recessions and a slow, inconsistent recovery thereafter. The decline is particularly notable for students who didn’t complete a four-year degree, a group that includes two-year college enrollees who have among the highest student loan default rates. [2]

Traditional economic theory tells us that individuals choose to invest in post-secondary education based on the expected costs and wage returns associated with the investment. But rapid and unforeseeable rises in prices and declines in college wage premia have contributed to decades of “unlucky” college-entry cohorts affected by a form of recessionary scarring . For example, a student who entered college in 2006 would have expected a sticker price of roughly $8,800 per year for a four-year college, but actually faced tuition of over $10,000 in their final year of college, a roughly 15% difference. This same student, upon graduation if they worked full time, would have earned about $3,500 less, on average, than what they would have expected upon entering. This example illustrates that many borrowers made sound borrowing decisions with available information, but as a result of these trends ended up with more debt than they could afford to pay off. [3] Consistent with this notion, the default rate for “unlucky” college entry cohorts of the 2000s is much higher than those of other cohorts, with undergraduate default rates doubling between 2000 and 2010: in 2017, 21 percent of undergraduate loan holders and 6 percent of graduate loan holders defaulted within 3 years ( CBO, 2020 ).

It is important to note that sticker prices for public institutions have declined 7 percent since 2021, the same period over which college wage premiums have been rising. Declining tuition, for the first time in decades, coincided with increased investment in higher education through pandemic-era legislation such as the American Rescue Plan, which allocated $40 billion in 2021 to support institutes of higher education and their students. Despite these improvements, as well as significant advances in the return on college investments over the last three years, many current borrowers still need some relief. The Administration has taken significant action to protect future cohorts from similar risks.

How the Administration is providing relief

Retrospective: Student Debt Relief Helps Existing Borrowers

In a commitment to help those who are overburdened with debt, the Administration has already approved Federal student debt cancellation for nearly 4 million Americans through various actions. Today , the Administration announced details of proposed rules that, if finalized as proposed, would provide relief to over 30 million borrowers when taken together with actions to date.

Importantly, much of this debt forgiveness comes from correcting program administration and improving regulations related to laws that were on the books before this Administration took office. This debt relief has affected borrowers from all walks of life, including nearly 900,000 Americans who have dedicated their lives to public service (such as teachers, social workers, nurses, firefighters, police officers, and others), borrowers who were misled and cheated by their institutions, and borrowers who are facing total or permanent disability, including many veterans. By relieving these borrowers of long-held, and in some cases very large burdens of debt, relief can have significant meaning and impact for borrowers, families, and their communities.

By reducing debtors’ liabilities, debt relief raises net worth (assets, including income less liabilities). Debt relief can also ease the financial burden of making payments—leading to greater disposable income for borrowers and their families, which enhances living standards and could positively influence decisions about employment, home buying, and mobility. While there are few direct estimates of the effect of debt cancelation in the literature, estimates based on the relationship between wealth and consumption suggest that this forgiveness could increase consumption by several billions of dollars each year in the next five to ten years.

Additionally, a recent study suggests that student debt cancellation can lead to increased earnings (due to greater geographic and career mobility), improved credit scores, and lower delinquency rates on other debts ( Di Maggio, Kalda, and Yao, 2019 ). This can facilitate access to capital for starting a business or buying a car or home. As home mortgages often require a certain debt-to-income ratio and depend heavily on credit scores, student debt cancellation could potentially increase home ownership. Indeed, based on the mechanical relationship between housing industry affordability standards and debt-to-income ratios, industry sources have suggested that those without student debt could afford to take out substantially larger mortgages ( Zillow, 2018 ). Other research also indicates a negative correlation between student loan debt and homeownership ( Mezza et al., 2020 ).

It is important to note that, while these pecuniary benefits are important, the benefits associated with debt relief are not merely financial. Experimental evidence has linked holding debt to heightened levels of stress and anxiety ( Drentea and Reynolds, 2012 ), worse self-reported physical health ( Sweet et al., 2013 ), and reduced cognitive capacity ( Robb et al., 2012 ; Ong et al., 2019 ). Studies also show that holding student debt can be a barrier to positive life cycle outcomes such as entrepreneurship ( Krishnan and Wang, 2019 ), and marriage ( Gicheva, 2016 ; Sieg and Wang, 2018 ). Student debt relief has the potential to improve these key outcomes for millions of borrowers.

Prospective: The SAVE Plan Helps Prevent Future Challenges

To address unaffordable education financing moving forward, the Administration has also introduced the Saving on a Valuable Education (SAVE) loan repayment program. The SAVE plan prospectively helps student borrowers by ensuring that once they graduate, they never have to pay more than they can afford towards their student loan debt. Importantly, the SAVE plan protects borrowers from being “unlucky” by ensuring that high tuition or low earnings do not result in loan payments that borrowers can’t afford. The CEA has detailed the real benefits of SAVE for borrowers in issue briefs and blogs , underscoring that SAVE is the most affordable student loan repayment program in U.S. history. By substantially reducing monthly payment amounts compared to previous income driven repayment (IDR) plans and reducing time to forgiveness to as little as 10 years for people who borrowed smaller amounts, the SAVE plan can mean tens of thousands of dollars in real savings for borrowers over the course of repayment.

Figure 2 gives the example of two representative borrowers. Take the first, a 4-year college graduate who has $31,000 in debt and earns about $40,500 per year. Under a standard repayment plan, this borrower would pay roughly $330 dollars each month for 10 years. Under SAVE, this borrower would pay about $50 per month for the first ten years, and on average about $130 per month for the next 10 years. Over a 20-year period, this borrower would make roughly $17,500 less in payments, not accounting for inflation over that period. This represents a 56 percent reduction in total payments compared to the standard repayment plan and includes considerable loan forgiveness. Similarly, the representative 2-year college graduate has $10,000 in debt and earns about $32,000 per year. Under a standard plan, this borrower would pay $110 dollars each month for 10 years. Under SAVE, this borrower would pay $0 per month for the first two years, and under $20 per month for the next eight years before their debt is forgiven at year 10. Overall, this borrower would be responsible for roughly $11,700 less in lifetime payments, not accounting for inflation. This borrower sees nearly 90 percent savings compared to the standard plan and receives considerable loan forgiveness.

SAVE can also have benefits beyond the individual borrower. More money in borrowers’ pockets due to lower payment obligations under SAVE could boost consumption and give borrowers breathing room to make payments on other debt. This consumption effect is bolstered by a large literature documenting the benefits of easing liquidity constraints (see, for example, Aydin, 2022 ; Parker et al., 2022 ). Additionally, by shortening time to forgiveness for undergraduate borrowers, SAVE can lead to positive debt-relief outcomes (as discussed above) for many more borrowers.

Another key aspect of income-driven repayment plans like SAVE is that they protect borrowers from having to make large payments when incomes are low. Specifically, the required payments are not based on the initial loan balance, but on one’s income and household size so that those cohorts who need to borrow more to pay for college do not make larger payments unless they make more income. SAVE also protects more of a borrower’s income as discretionary and, when the full plan is implemented in Summer 2024, will limit monthly payments on undergraduate loans to 5 percent of discretionary income. In fact, for single borrowers who make less than $33,000 per year, the required monthly payments will be zero dollars. From a finance perspective, the SAVE plan provides a form of insurance against tuition spikes and economic downturns–taking some of the risk out of investing in one’s education while also bringing costs down.   

A common concern, and one that could mute these benefits, is that increases in the generosity of education financing may encourage institutions to raise tuition and fees in response, a phenomenon commonly referred to as the Bennett Hypothesis (for an excellent overview of research, see Dynarski et al., 2022 ). Theoretically, in a market when sellers are maximizing profits, any policy that increases demand will also increase prices. However, this is less likely to impact the over 70% of U.S. undergraduates who attend public colleges, which are not profit-driven and often have statutorily set tuition. Consistent with this notion, the evidence in support of the Bennett Hypothesis primarily comes from for-profit colleges, which are highly reliant on students who receive federal financial aid ( Cellini and Goldin, 2014 ; Baird et al, 2022 ). [4] Importantly, although the for-profit sector enrolls some of the country’s most vulnerable students, enrollment in the sector in 2021 accounted for only 5 percent of total undergraduate enrollment, suggesting that aggregate tuition increases in response to changes in education financing may be modest. Furthermore, the Biden-Harris Administration has taken action to crack down on for-profit colleges that take advantage of, or mislead, their students. And, recent regulations, such as the Gainful Employment ( GE ) rule, add safeguards against unaffordable debt regardless of more generous education financing. 

Although the SAVE plan stands to benefit borrowers of all backgrounds, the plan has important racial and socioeconomic equity implications because it is particularly beneficial for those borrowers with the lowest incomes. Centuries of inequities have led to Black, Hispanic, and Native households being more likely than their White peers to fall in the low end of the income distribution. This means that, mechanically, the SAVE plan’s benefits could accrue disproportionately to these groups. Indeed, using completion data from recent years, an Urban Institute analysis estimates that 59 percent of credentials earned by Black students and 53 percent of credentials earned by Hispanic students are likely to be eligible for some amount of loan forgiveness under SAVE, compared to 42 percent of credentials earned by White students ( Delisle and Cohn, 2023 ). Finally, the interest subsidy described in an August 2023 CEA blog , prevents ballooning balances when a borrower cannot cover their entire monthly interest payment, a phenomenon that has historically led to many borrowers in general, and Black borrowers in particular, to see loan balances that are higher than their original loan amount, even several years out from graduating with a bachelor’s degree ( NCES, 2023 ).

Broader economic impacts

The benefits associated with SDR and SAVE for millions of Americans are considerable. In the short run, under both SDR and SAVE, those who receive relief may be able to spend more in their communities and contribute to their local economies. Summing the likely consumption effects of the Administration’s student debt relief and SAVE programs results in billions of dollars in additional consumption annually. Despite the modest effect on the macroeconomy as a whole (note that the U.S. economy is roughly $28 trillion with a population of roughly 320 million), these consumption effects represent incredibly meaningful impacts on individual borrowers’ financial security and the economic wellbeing of their communities.

SAVE, because it brings down the cost of taking out loans to go to college, has the potential to lead to longer-term economic growth if it leads to greater educational attainment. This increased attainment can occur both through improved retention and completion of post-secondary education, and also the movement of students into college who would not have otherwise enrolled. There is a long macroeconomics literature linking educational attainment in a nation to GDP growth (see, for example, Lucas, 1988 ; Hanushek and Woesmann, 2008 ). While identifying the causal effect of schooling on GDP is challenging, researchers, using a variety of approaches, find that a one-year increase in average education (for the entire working population) would increase the real GDP level by between 5 and 12 percent ( Barro and Lee, 2013 ; Soto, 2002 ) —a result that is in line with the micro-founded relationship between years of education and earnings ( Lovenheim and Smith, 2022 ).

To put this relationship in perspective and highlight the growth potential of increasing educational attainment, the CEA simulated the hypothetical effect on GDP of increasing the college-going rate by 1, 3, and 5 percentage points, respectively. This range represents the kinds of changes in college going that have been observed over several years: the college enrollment rate for 18- to 24-year-olds declined 4 percentage points between 2011 and 2021 after increasing by 6 percentage points between 2000 and 2011 ( NCES 2023 ). CEA simulations show that by 2055, a policy that increased the college going rate by 1, 3, and 5 percentage points could increase the level of GDP in 2055 (thirty years from now) by 0.2, 0.6, and 1 percent respectively. This represents hundreds of billions of dollars of additional economic activity in the long run.

While increased growth is an exciting possibility, it would only occur insofar as SAVE leads to increased educational attainment, which is uncertain. The academic literature has found that student loans can promote academic performance ( Barr, et. al. 2021 ), and increase educational attainment by increasing transfers from 2-year to 4-year colleges and increasing college completion among enrollees ( Marx and Turner, 2019 ). At the same time, increases in college-going due to SAVE are by no means guaranteed. While, historically, policies that reduce the cost of college through direct means—such as providing students with generous grant aid, or reducing tuition—have succeeded at raising college enrollment levels ( Dynarski, 2003 ; Turner, 2011 ), a pair of recent studies show that prospective students may only respond to cost changes when they are salient, i.e., they are framed and marketed in the right way ( Dynarski et al., 2021 ), and relatively certain ( Burland et al., 2022 ). However, evidence suggests that there is demand for plans like SAVE ( Balakrishnan et al., 2024 ), particularly as SAVE can provide sizable benefits to borrowers in terms of reducing their long-term debt burden and keep monthly payments low (dependent on a borrower’s income) after they finish school.

This highlights the importance of communicating the benefits of the SAVE program to prospective students who otherwise would not enroll in college due to cost concerns, including potential barriers to paying off student loans in the future. Doing so could lead to meaningful increases in college enrollment, and the resulting improvements in productive capacity could increase the size of the U.S. economy for years to come.

Concluding remarks

The Biden-Harris Administration has taken bold action to address a student debt problem that has been decades in the making. This student debt cancellation will provide well-deserved relief for borrowers who have paid their fair share, many of whom had the proverbial rug pulled out from under them with concurrent rapidly rising tuition and declining returns to a college degree. The relief has and will improve economic health and wellbeing of those who have devoted years of their life to public service, those who were defrauded or misled by their institutions, and those who have been doing all they can to make payments, but have still seen their loan balances grow. Looking to future generations, the Administration implemented the SAVE plan to protect borrowers against tuition spikes and poorer than expected labor market outcomes that often plague students graduating into a period of economic downturn ( Rothstein, 2021 ; Schwandt and von Wachter, 2023 ).

Both student debt relief and SAVE will enhance the economic status of millions of Americans with student debt: enable them to allocate more funds towards basic necessities, take career risks, start businesses, and purchase homes with the understanding that they will never have to pay more than they can afford towards their student loans. Moreover, the SAVE plan makes repayment more affordable for future generations, which helps borrowers manage monthly payments, but also enables more people from all walks of life to explore their full potential and pursue higher education, enhancing the potential of the U.S. workforce and the economy more broadly. 

[1] In 2021, 51% of total undergraduates attended public 4-year universities and 21% attended public 2-years in 2021.

[2] The BA group excludes those with a graduate degree, or any education beyond a bachelor’s degree.

[3] Recent research shows that, despite a positive return on investment (ROI) for many, including the average student, the distribution of ROI has widened over the last several decades such that the likelihood of negative ROI is higher than it has historically been, particularly so for underrepresented minority students ( Webber 2022 ).

[4] There is also some evidence in support of the Bennett Hypothesis at the graduate level ( Black et al. 2023 ).

Stay Connected

We'll be in touch with the latest information on how President Biden and his administration are working for the American people, as well as ways you can get involved and help our country build back better.

Opt in to send and receive text messages from President Biden.

University research seed funding awarded to Engineering faculty

Thirty-three Brown researchers, including ten from the School of Engineering, are receiving University research awards through 22 Research Seed grants. This annual program is aimed at helping early-stage research projects grow. Research seed funding is competitively awarded annually by the Office of the Vice President for Research and helps faculty more successfully advance competitive research proposals by supporting the generation of preliminary data, pursuing new directions or collaborations in research, and other endeavors. Competitive proposals for sizable projects are expected to be submitted to an external funding organization within a year of the completion of the research seed fund period. Projects from the School of Engineering include: Nora Ayanian and Kenny Breuer , who are researching “Data-driven stabilization of close-proximity quadrotor flight”; Lucas Caretta and Miguel Bessa for a project titled “Data-driven design of a low power, nanoscale neural network using non-linear spin-wave interference ”; Nitin Padture who is researching “Emergent mechanical behavior of charged hetero-interfaces in solar cells ”; Eric Suuberg and Franklin Goldsmith for the project titled “ A novel route for destroying ‘forever chemicals ’”; and Eric Darling , Anita Shukla and Edith Mathiowitz , who are researching “ Long-circulating vascular treatment for life-threatening bloodstream infections .”  

Data-driven stabilization of close-proximity quadrotor flight

Quadrotor flying vehicles (“drones”) are finding widespread use in many applications including search and rescue, remote monitoring, inspection in agricultural and industrial settings, and operations in hazardous or even extra-terrestrial environments.  One critical weakness in this exciting new arena is the inability to operate dense swarms of quadrotors due to aerodynamic interference of the rotor wakes. This weakness also prevents many new and advanced applications such as synthetic aperture imaging or cooperative assembly tasks. The goal of this project is to acquire data on multi-quadrotor interactions – force,  torque and velocity interactions – over a wide range of operating conditions and spatial separation, and to use data-driven analysis techniques to develop efficient, accurate and practical flight controllers to compensate for the close-proximity interference. Despite the importance of this problem to advanced flight robotics, there has been little work presented in this area. The collaboration between professors Breuer and Ayanian -- who bring expertise from the aerodynamic and computer science fields – presents an opportunity to put Brown at the forefront of high density cooperative drone flight control. The results from this effort will provide significant first steps necessary for the PIs to apply for longer-term, more substantial funding from government agencies (NSF, DARPA, NASA, etc) and private industry. Intellectual property related to the aerodynamic design and control of drone swarms, as well as trajectory planning for complex swarm maneuvers is anticipated. PI: Kenneth Breuer , Professor of Engineering Co-PI: Nora Ayanian , Associate Professor of Computer Science and Engineering  

Data-driven design of a low power, nanoscale neural network using non-linear spin-wave interference

Semiconductor technologies are rapidly facing challenges in scalability, energy consumption, and reduced latency. These challenges are driving a significant effort to develop alternatives to CMOS-based technologies to meet the demands of future computing technologies. Neuromorphic computing could address these challenges with high performance and low-power artificial neural networks. These technologies can provide increased computing performance with enhanced features and reduced cost but rely on traditional chip technologies not designed for their operation. This collaboration seeks to develop a first of its kind spin wave neural network comprised of two-dimensional magnon scattering centers, also known as magnonic crystals. We hypothesize that by using inverse design machine learning processes and high throughput micromagnetic simulations, we will optimize the array of spin wave scattering sites to create a neural network capable of number classification based on spin wave interference patterns. In this collaborative proposal, our interdisciplinary team will test our hypothesis and address design challenges associated with the vast optimization parameter space by developing a coherent computation, materials synthesis and characterization, and spin wave imaging platform. This platform will enable a learning loop, where the prediction and discovery of unique magnonic crystal topologies will be reinforced by feedback from micromagnetic simulations and experimental verification via novel quantum imaging platforms. The outcomes of this project include a framework and design protocol by which to optimize spin wave scattering platforms for advanced computing, new fundamental insight on spin wave-spin wave interactions, and the experimental realization of a low power spin wave neural network. PI: Lucas Caretta , Assistant Professor of Engineering Co-PI: Miguel Bessa , Associate Professor of Engineering  

Emergent mechanical behavior of charged hetero-interfaces in solar cells

Interfaces between dissimilar materials (semiconductors, dielectrics, metals) are ubiquitous in multi-layered energy-conversion and -storage devices, such as solar cells and batteries. The reliability of these devices critically depends on the mechanical adhesion at these interfaces. Since most of these functional devices are ‘dynamic,’ during their operation under external stimuli (electric field, light) many hetero-interfaces typically accumulate charged species (electrons, holes, vacancies, interstitials), thereby generating internal charged layers. Unfortunately, to-date the charged-interface effects have not been considered explicitly in the adhesion and fracture of interfaces in these devices. The proposed research will focus on the burgeoning perovskite solar cells (PSCs) where such effects are expected to be critical for their long-term durability and reliability. The objective is to develop experimental tools for gaining fundamental understanding of the important effects of accumulated charge and external stimuli (electric field, light) on the adhesion and fracture behavior of a range of hetero-interfaces relevant to PSCs. This will address the wide knowledge gap in this important area, and help take materials science of adhesion to the next level, leading to discovery of hitherto unknown electro-photo-mechanical coupled phenomena. The basic tools and understanding developed here can be extended to the study of other energy-related devices (batteries, fuel cells, supercapacitors) for an outsized impact. The results from the proposed seed project will serve as preliminary data for at least two sustainable-energy-related proposals being developed by PI and his colleagues for submission to external agencies. PI: Nitin Padture , Otis Everett Randall University Professor of Engineering  

A novel route for destroying “forever chemicals”

There is growing concern regarding chemical compounds from the per- and poly-fluoroalkyl substances (PFAS) family of industrially produced materials. They offer many possibilities for human exposure, and there is increasing concern, regarding negative health effects from such exposures. The term “forever chemicals” has been applied to these materials because many in this class of compounds do not break down in the natural environment. Allowable regulatory levels for PFAS in drinking water are now in the parts per trillion range. Because there is no easy method to break these chemicals down this has led to widespread adoption of carbon adsorption technologies to remove them from water. While this removes the PFAS from drinking water, they remain in the activated carbon, which cannot be dumped in landfills. The PFAS need to be destroyed, which has often involved incineration of the PFAS-containing carbons. Hazardous waste incinerators are unpopular and difficult to operate, and there is a desire to identify alternate destruction technologies. Recent work at Brown has identified the particular chemical species which make incineration effective, and other much older work (from the coal liquefaction field) points to the possibility of designing a completely different PFAS destruction technology. What is proposed is a laboratory demonstration of the new technology. A successful demonstration would allow follow-on proposals to any of a number of agencies all of whom are interested in the problem of PFAS destruction (e.g., EPA, DOD- through its SERDP and ESTCP programs, NSF). PI: Eric Suuberg , C.V. Starr Professor of Technology Entrepreneurship, Professor of Engineering Co-PI: Franklin Goldsmith , Associate Professor of Engineering  

Long-circulating vascular treatment for life-threatening bloodstream infections

The goal of this project is to demonstrate feasibility for a long-circulating treatment targeting bacterial toxins that contribute to the debilitating effects of bloodstream infection (BSI). Technologies developed in the participating investigators’ laboratories will be combined as a novel solution to the problem. Shukla brings expertise in creating nanoparticle formulations that are responsive to bacterial virulence factors, such as hemolysins. Lipid vesicle nanoparticle formulations developed by Shukla will be combined with a technology developed by Darling and Mathiowitz, hyper-compliant microparticles (HCMPs), that hold great promise as long-circulating vascular carriers. HCMPs are spherical hydrogel microparticles sized similarly to white blood cells but with an extremely low elastic modulus that allows them to squeeze through small constrictions in the vasculature. The primary goals of the proposed project are to 1) develop a hemolysin-sorbent HCMP using red blood cell (RBC) membrane-derived nanoparticle vesicles for reducing RBC morbidity associated with BSIs and 2) assess HCMP persistence, biodistribution, and ultimate fate in an in vivo model. A combination of in vitro and in vivo experiments will be completed to achieve these goals. The anticipated findings will lay the groundwork for a larger project and external proposal to demonstrate the therapeutic effectiveness of continuously circulating HCMPs that contain hemolysin-sorbent nanoparticles for ameliorating the negative impact of BSI. PI: Eric M. Darling , Associate Professor of Medical Science, Associate Professor of Engineering, Associate Professor of Orthopaedics Co-PI: Anita Shukla , Elaine I. Savage Associate Professor of Engineering Co-PI: Edith Mathiowitz , Professor of Pathology and Laboratory Medicine, Professor of Engineering

An official website of the United States government

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

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

• Publications
• Account settings

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

• Advanced Search
• Journal List
• Indian J Anaesth
• v.60(9); 2016 Sep

How to write a research proposal?

Department of Anaesthesiology, Bangalore Medical College and Research Institute, Bengaluru, Karnataka, India

Devika Rani Duggappa

Writing the proposal of a research work in the present era is a challenging task due to the constantly evolving trends in the qualitative research design and the need to incorporate medical advances into the methodology. The proposal is a detailed plan or ‘blueprint’ for the intended study, and once it is completed, the research project should flow smoothly. Even today, many of the proposals at post-graduate evaluation committees and application proposals for funding are substandard. A search was conducted with keywords such as research proposal, writing proposal and qualitative using search engines, namely, PubMed and Google Scholar, and an attempt has been made to provide broad guidelines for writing a scientifically appropriate research proposal.

INTRODUCTION

A clean, well-thought-out proposal forms the backbone for the research itself and hence becomes the most important step in the process of conduct of research.[ 1 ] The objective of preparing a research proposal would be to obtain approvals from various committees including ethics committee [details under ‘Research methodology II’ section [ Table 1 ] in this issue of IJA) and to request for grants. However, there are very few universally accepted guidelines for preparation of a good quality research proposal. A search was performed with keywords such as research proposal, funding, qualitative and writing proposals using search engines, namely, PubMed, Google Scholar and Scopus.

Five ‘C’s while writing a literature review

BASIC REQUIREMENTS OF A RESEARCH PROPOSAL

A proposal needs to show how your work fits into what is already known about the topic and what new paradigm will it add to the literature, while specifying the question that the research will answer, establishing its significance, and the implications of the answer.[ 2 ] The proposal must be capable of convincing the evaluation committee about the credibility, achievability, practicality and reproducibility (repeatability) of the research design.[ 3 ] Four categories of audience with different expectations may be present in the evaluation committees, namely academic colleagues, policy-makers, practitioners and lay audiences who evaluate the research proposal. Tips for preparation of a good research proposal include; ‘be practical, be persuasive, make broader links, aim for crystal clarity and plan before you write’. A researcher must be balanced, with a realistic understanding of what can be achieved. Being persuasive implies that researcher must be able to convince other researchers, research funding agencies, educational institutions and supervisors that the research is worth getting approval. The aim of the researcher should be clearly stated in simple language that describes the research in a way that non-specialists can comprehend, without use of jargons. The proposal must not only demonstrate that it is based on an intelligent understanding of the existing literature but also show that the writer has thought about the time needed to conduct each stage of the research.[ 4 , 5 ]

CONTENTS OF A RESEARCH PROPOSAL

The contents or formats of a research proposal vary depending on the requirements of evaluation committee and are generally provided by the evaluation committee or the institution.

In general, a cover page should contain the (i) title of the proposal, (ii) name and affiliation of the researcher (principal investigator) and co-investigators, (iii) institutional affiliation (degree of the investigator and the name of institution where the study will be performed), details of contact such as phone numbers, E-mail id's and lines for signatures of investigators.

The main contents of the proposal may be presented under the following headings: (i) introduction, (ii) review of literature, (iii) aims and objectives, (iv) research design and methods, (v) ethical considerations, (vi) budget, (vii) appendices and (viii) citations.[ 4 ]

Introduction

It is also sometimes termed as ‘need for study’ or ‘abstract’. Introduction is an initial pitch of an idea; it sets the scene and puts the research in context.[ 6 ] The introduction should be designed to create interest in the reader about the topic and proposal. It should convey to the reader, what you want to do, what necessitates the study and your passion for the topic.[ 7 ] Some questions that can be used to assess the significance of the study are: (i) Who has an interest in the domain of inquiry? (ii) What do we already know about the topic? (iii) What has not been answered adequately in previous research and practice? (iv) How will this research add to knowledge, practice and policy in this area? Some of the evaluation committees, expect the last two questions, elaborated under a separate heading of ‘background and significance’.[ 8 ] Introduction should also contain the hypothesis behind the research design. If hypothesis cannot be constructed, the line of inquiry to be used in the research must be indicated.

Review of literature

It refers to all sources of scientific evidence pertaining to the topic in interest. In the present era of digitalisation and easy accessibility, there is an enormous amount of relevant data available, making it a challenge for the researcher to include all of it in his/her review.[ 9 ] It is crucial to structure this section intelligently so that the reader can grasp the argument related to your study in relation to that of other researchers, while still demonstrating to your readers that your work is original and innovative. It is preferable to summarise each article in a paragraph, highlighting the details pertinent to the topic of interest. The progression of review can move from the more general to the more focused studies, or a historical progression can be used to develop the story, without making it exhaustive.[ 1 ] Literature should include supporting data, disagreements and controversies. Five ‘C's may be kept in mind while writing a literature review[ 10 ] [ Table 1 ].

Aims and objectives

The research purpose (or goal or aim) gives a broad indication of what the researcher wishes to achieve in the research. The hypothesis to be tested can be the aim of the study. The objectives related to parameters or tools used to achieve the aim are generally categorised as primary and secondary objectives.

Research design and method

The objective here is to convince the reader that the overall research design and methods of analysis will correctly address the research problem and to impress upon the reader that the methodology/sources chosen are appropriate for the specific topic. It should be unmistakably tied to the specific aims of your study.

In this section, the methods and sources used to conduct the research must be discussed, including specific references to sites, databases, key texts or authors that will be indispensable to the project. There should be specific mention about the methodological approaches to be undertaken to gather information, about the techniques to be used to analyse it and about the tests of external validity to which researcher is committed.[ 10 , 11 ]

The components of this section include the following:[ 4 ]

Population and sample

Population refers to all the elements (individuals, objects or substances) that meet certain criteria for inclusion in a given universe,[ 12 ] and sample refers to subset of population which meets the inclusion criteria for enrolment into the study. The inclusion and exclusion criteria should be clearly defined. The details pertaining to sample size are discussed in the article “Sample size calculation: Basic priniciples” published in this issue of IJA.

Data collection

The researcher is expected to give a detailed account of the methodology adopted for collection of data, which include the time frame required for the research. The methodology should be tested for its validity and ensure that, in pursuit of achieving the results, the participant's life is not jeopardised. The author should anticipate and acknowledge any potential barrier and pitfall in carrying out the research design and explain plans to address them, thereby avoiding lacunae due to incomplete data collection. If the researcher is planning to acquire data through interviews or questionnaires, copy of the questions used for the same should be attached as an annexure with the proposal.

Rigor (soundness of the research)

This addresses the strength of the research with respect to its neutrality, consistency and applicability. Rigor must be reflected throughout the proposal.

It refers to the robustness of a research method against bias. The author should convey the measures taken to avoid bias, viz. blinding and randomisation, in an elaborate way, thus ensuring that the result obtained from the adopted method is purely as chance and not influenced by other confounding variables.

Consistency

Consistency considers whether the findings will be consistent if the inquiry was replicated with the same participants and in a similar context. This can be achieved by adopting standard and universally accepted methods and scales.

Applicability

Applicability refers to the degree to which the findings can be applied to different contexts and groups.[ 13 ]

Data analysis

This section deals with the reduction and reconstruction of data and its analysis including sample size calculation. The researcher is expected to explain the steps adopted for coding and sorting the data obtained. Various tests to be used to analyse the data for its robustness, significance should be clearly stated. Author should also mention the names of statistician and suitable software which will be used in due course of data analysis and their contribution to data analysis and sample calculation.[ 9 ]

Ethical considerations

Medical research introduces special moral and ethical problems that are not usually encountered by other researchers during data collection, and hence, the researcher should take special care in ensuring that ethical standards are met. Ethical considerations refer to the protection of the participants' rights (right to self-determination, right to privacy, right to autonomy and confidentiality, right to fair treatment and right to protection from discomfort and harm), obtaining informed consent and the institutional review process (ethical approval). The researcher needs to provide adequate information on each of these aspects.

Informed consent needs to be obtained from the participants (details discussed in further chapters), as well as the research site and the relevant authorities.

When the researcher prepares a research budget, he/she should predict and cost all aspects of the research and then add an additional allowance for unpredictable disasters, delays and rising costs. All items in the budget should be justified.

Appendices are documents that support the proposal and application. The appendices will be specific for each proposal but documents that are usually required include informed consent form, supporting documents, questionnaires, measurement tools and patient information of the study in layman's language.

As with any scholarly research paper, you must cite the sources you used in composing your proposal. Although the words ‘references and bibliography’ are different, they are used interchangeably. It refers to all references cited in the research proposal.

Successful, qualitative research proposals should communicate the researcher's knowledge of the field and method and convey the emergent nature of the qualitative design. The proposal should follow a discernible logic from the introduction to presentation of the appendices.

Financial support and sponsorship

Conflicts of interest.

There are no conflicts of interest.

• Skip to main content
• Skip to FDA Search
• Skip to in this section menu
• Skip to footer links

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.

U.S. Food and Drug Administration

•   Search
•   Menu
• FDA Organization
• Center for Drug Evaluation and Research | CDER

CDER Center for Clinical Trial Innovation (C3TI)

Bayesian Supplemental Analysis (BSA) Demonstration Project

C3TI aims to increase experience in Bayesian statistical methods in simple trial settings across sponsors, CDER clinical reviewers, and CDER statisticians, including deepening an understanding of their applicability, opportunities, and challenges. Bayesian statistical approaches can offer different perspectives in the assumptions made or addressed for an analysis when compared to frequentist approaches. Areas with emerging use of Bayesian methods include early-phase trials, trials with complex adaptive designs, and trials that incorporate borrowing of prior information, such as pediatric trials. 

With the Bayesian Supplemental Analysis (BSA) demonstration project, C3TI will partner with sponsors to integrate Bayesian analysis in parallel to frequentist analysis during their trial, providing an opportunity for both CDER and sponsors to learn new methods without impacting review criteria. In contrast to the Complex Innovative Design (CID) Program (more information is available on the CID Program webpage ), this demonstration project focuses on simple non-adaptive trial designs that do not incorporate data from previous trials. In addition, during the review of trials participating in this demonstration project, the Bayesian analyses would be supplementary descriptive analyses that would not change the primary analysis methods or decision criteria (e.g., frequentist null hypothesis testing at 1-sided 0.025) for the trial. Increasing the experience and understanding of Bayesian approaches when used as supplementary analyses in an experiment-friendly environment may facilitate their use as primary analyses in appropriate settings in the future.  

Advance understanding and use of Bayesian statistics

This demonstration project seeks to advance the understanding of Bayesian statistical methods and establish processes for integrating these approaches into clinical trial design in the future (e.g., processes for pre-aligning on specifications of prior distributions), which would be shared with parties across the drug development landscape to drive appropriate adoption of Bayesian statistical methods. For consideration and selection to participate within this demonstration project, the trial must be a phase 3 efficacy, safety, or non-inferiority standalone trial (i.e., not incorporating data from previous trials beyond informing the non-inferiority margin) with a simple non-adaptive design. The Bayesian analysis should supplement the primary analysis and may be used to evaluate the primary endpoint in the overall study population and/or in relevant subgroups (i.e., for subgroup analysis). Participating sponsors would support the conduct of the supplementary descriptive Bayesian analyses.

Benefits of participation

Please note that sponsors who are interested in a trial with a Bayesian primary analysis may reach out to C3TI through the program mailbox to be directed to the proper subject matter experts for support.

Sponsors and other industry parties who are willing to participate in this demonstration project will benefit from demonstrating the value of Bayesian methods in drug development, testing new analytical methods in an experiment-friendly environment without impacting the regulatory decision, and partnering with additional FDA/CDER subject matter experts on Bayesian statistics. Furthermore, by participating, sponsor(s) would receive additional CDER support to reach alignment on the statistical analysis plan for the supplemental Bayesian analysis. See an example statistical analysis plan for a supplemental Bayesian analysis .  

Eligibility Criteria for BSA Demonstration Project Proposals

• The sponsor has an active pre-Investigational New Drug (IND) or IND for the product(s) included in the proposal.
• The trial must be a phase 3 efficacy, safety, or non-inferiority standalone trial (i.e., not incorporating data from previous trials beyond informing the non-inferiority margin) with a simple non-adaptive design.
• The Bayesian analysis should supplement the primary analysis and may be used to evaluate the primary endpoint in the overall study population and/or in relevant subgroups (i.e., for subgroup analysis). Participating sponsors would support the conduct of the supplementary descriptive Bayesian analyses.
• Sponsors participating in demonstration projects will be expected to share select details of their clinical trials and the implementation of clinical trial innovations as they progress, starting as early as the finalization of study design. This sharing may include updates, lessons learned, and relevant insights gathered during the trial. It is understood that these shared details will reflect general principles and innovative aspects, while maintaining the necessary confidentiality of proprietary or sensitive information.

Instructions on how to submit a proposal can be found on the C3TI Demonstration Program Proposal Submission webpage.