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How To Write Clear Research Questions And Hypotheses

Quick Takeaways:

• et al.' means 'and others'.
• Use 'et al.' to cite works with three or more authors.
• The presentation (et al., et al., or rarely et al) depends on the style guide or journal guidelines

The English language has a rich history of borrowing words from other languages, especially from Latin. Latin abbreviations such as ‘a.m.’, ‘p.m.’ and ‘CV’ have become part of our everyday vocabulary. Such abbreviations are also frequently used in academic writing, from the ‘Ph.D.’ in the affiliation section to the ‘i.e.’, ‘e.g.’, ‘et al.’, and ‘QED’ in the rest of the paper.

This guide explains when and how to correctly use ‘et al.’ in a research paper.

In this guide:

• 1) Meaning of ‘et al.’
• a) Table: Correct use of ‘et al.’ by style guide
• b) Unusual scenarios

In  previous blogs  we have already covered how to write an introduction and literature review, and how to define the purpose and rationale for your study.

Depending on your field, you may need to write your research question and/or hypothesis before moving on to write the main body of your study. You don’t usually need to include both research question and hypothesis, unless you have several hypotheses that arise from the research question.

Important!  We are not suggesting that you come up with your research question or hypotheses at this stage: Your research question or hypotheses should actually have been developed before you conducted or even designed your study.

Here, we’re discussing how you can clearly state the research question or hypotheses.

What is a Research Question?

Your research question, or questions, should specifically state the purpose of your study in terms of the question you aim to answer. Its purpose is to guide and center your research study.

For example: If the purpose of your study is to evaluate the efficacy of a newly-developed intervention for treating anxiety, your research question might be something like:

“Is intervention A effective for treating people with anxiety?”

The research question above needs to be turned into a testable hypothesis. A hypothesis is a statement rather than a question, and it should make a  prediction  about what you expect to happen. This is referred to as a  directional  or  alternative hypothesis , and is often abbreviated as H 1 .

Continuing with the research question example above, the hypothesis might be written as:

“Participants who receive intervention A will show a significant reduction in scores on the Anxiety Scale from baseline to 6-week follow up.”

If your study uses a control group, the hypothesis can be modified to:

“Participants who receive intervention A will score significantly lower on the Anxiety Scale than participants in the wait-list control group.”

Bear in mind that  your hypothesis needs to be specific .

Continuing with the earlier example, if your hypothesis only states  “Participants who receive the intervention will be less anxious” , it is not specific enough because it does not state how you will know whether anxiety has been reduced or what “less” is in relation to.

Filling a Gap is Not a Rationale in itself

When you test a hypothesis, you actually  test the null hypothesis , which predicts no difference in the variables you are testing.

Some journals prefer you to state the null hypothesis, often abbreviated as H 0 , or both the null and alternative.

The corresponding null forms of our example hypotheses are:

“Participants who receive intervention A will show no difference in anxiety scores from baseline to 6-week follow-up.”

“Participants who receive intervention A will show no difference in anxiety scores from participants in the wait-list control group.”

More examples of Research Questions and Hypotheses

Your research questions and hypotheses are likely to be quite different from our examples depending on the type of your study. We present some examples below for your reference.

Case 1:  Experimental study examining the effect of one (or more) independent variable(s) on a dependent variable Research Question:   “Does substance A affect the appetite of rats?” Directional or Alternative Hypothesis:   “Rats that receive an injection of substance A will consume significantly more food than rats that do not receive the injection.” Null Hypothesis:   “Rats that receive an injection of substance A will show no difference in food consumption from those that do not receive the injection.”

Case 2:  Correlational study examining the relationships among variables Research Question:   “Does spending time outdoors influence how satisfied people feel with their lives?” Directional or Alternative Hypothesis:   “There is a significant positive relationship between the weekly amount of time spent outdoors and self-reported levels of satisfaction with life.” Null Hypothesis:   “There is no relationship between the weekly amount of time spent outdoors and self-reported levels of satisfaction with life.”

Tips when you are writing several hypotheses, or stating both the null and alternative in your paper

I.  It is clearer to the reader if you make the wording for your hypotheses as similar as possible to each other. So, use the same key phrases and terms: rather than making the writing more interesting, varying the use of key terms always causes confusion.

II.  Try to position the variables so that the independent variable appears first in the sentence, then the dependent variable. This word order reflects the hypothesised direction of the effect and is therefore clearer than the reverse order.

• “Significantly more food will be consumed by rats that receive an injection of substance A than by rats that do not receive the injection.”
• “Rats that receive an injection of substance A will consume significantly more food than rats that do not receive the injection.”

QUICK ASIDE

Wondering why some abbreviations such as ‘et al.’ and ‘e.g.’ use periods, whereas others such as CV and AD don’t? Periods are typically used if the abbreviations include lowercase or mixed-case letters. They’re usually not used with abbreviations containing only uppercase letters.

Unusual Scenarios

Our latest online workshop built on the success of face-to-face workshops we developed specifically for local universities. Over 30 faculty members joined the session, presented by our Chief Operating Officer, Mr Nick Case, to learn from our case studies on editing research proposals.

The response to our workshop, which included a constructive and insightful Q&A session, was very positive.Drawing on our extensive experience working with hundreds of Hong Kong researchers targeting the GRF and ECS every year, we used examples of poor and subsequently improved proposals to show the attendees how they can make their applications stand out. The response to our workshop, which included a constructive and insightful Q&A session, was very positive.Drawing on our extensive experience working with hundreds of Hong Kong researchers targeting the GRF and ECS every year, we used examples of poor and subsequently improved proposals to show the attendees how they can make their applications stand out. The response to our workshop, which included a constructive and insightful Q&A session, was very positive.Drawing on our extensive experience working with hundreds of Hong Kong researchers targeting the GRF and ECS every year, we used examples of poor and subsequently improved proposals to show the attendees how they can make their applications stand out.

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• 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 August 15, 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 .

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See an example

Step 1. Ask a question

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

Step 2. Do some preliminary research

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

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

Step 3. Formulate your hypothesis

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

4. Refine your hypothesis

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

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

5. Phrase your hypothesis in three ways

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

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

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

6. Write a null hypothesis

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

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

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

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

 Statistics

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

Research bias

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

Prevent plagiarism. Run a free check.

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.

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McCombes, S. (2023, August 15). How to Write a Strong Hypothesis | Steps & Examples. Scribbr. Retrieved September 27, 2023, from https://www.scribbr.com/methodology/hypothesis/

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Q. How do I write a good hypothesis statement?

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Answered By: APUS Librarians Last Updated: Jun 05, 2023     Views: 311959

Start by understanding just what a hypothesis is! Generally used in quantitative research studies, it's an educated guess or prediction about the relationship between two variables . It must be a testable statement...something that you can support or falsify with observable evidence .

• Take some time to review this brief tutorial for a simple explanation.
• If you need still more detail, visit the SAGE Research Methods Map . 

A good hypothesis will be written as a statement or question that specifies:

• The dependent variable(s): who or what you expect to be affected
• The independent variable(s): who or what you predict will affect the dependent variable
• What you predict the effect will be.

See some examples:

• A Strong Hypothesis
• Constructing a Hypothesis
• How to Write a Research Question

Note: if you are designing a research study , explore the Research Methods  section of the library for helpful resources.  

See also:   What is the difference between a thesis statement and a hypothesis statement?

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

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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.

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Problem statement and hypothesis

A problem statement may need to be re-worked throughout the process .

The academic problem that you are investigating in your assignment can either take the form of a problem statement, i.e. a question that you want to answer, or it can be a hypothesis that you wish to reject or confirm. How you formulate the problem influences the task you are embarking on. Problem statements as well as hypotheses must be relevant to your area of study, and you must be able to carry out the investigation using the resources and methods available to you.  

Note that a problem statement or a hypothesis often changes during the writing process. Sometimes you have to change the focus of the problem statement/hypothesis, and sometimes you only have to change a single word. The amount of changes required depends on your study programme and the assignment at hand. Therefore, you should always ask your teacher or supervisor for advice.  

Problem statement

A problem statement usually consists of one question to be addressed in your assignment and to be answered in your conclusion. It can include 2-5 sub-questions. A problem statement can take different forms, but generally: 

It uses accurate wording, for example technical terms 

It relates specifically to your project, describing what you want to study (object) and how you want to study it (theories and methods)  

It not only introduces a description of the problem (what is the problem?) but also encourages explanation, reflection and discussion of the problem (how and why does the problem exist?) 

The problem statement as a guiding tool

The problem statement can be a useful tool to guide you through your work process. Whether you are collecting empirical data, searching for literature or reading, always keep your problem statement in mind. This will help you narrow down your searches and your reading, and help you focus on what is relevant in order to answer the question in your problem statement. 

You should also be prepared to revise your problem statement as you go along. For example if you discover a more relevant or interesting question when you start working on the investigation. Always discuss with your teacher or supervisor if you want to make radical changes to your problem statement, and thereby to your assignment.  

Working on your problem statement

The problem statement sets the framework for your assignment .

Your problem statement asks the question that will be answered in the conclusion. The actual assignment - between the problem statement and the conclusion - addresses your main question. There must be a clear link between the problem statement and the conclusion. 

A problem statement must comply with certain specific requirements 

Your problem statement has to meet a number of formal requirements, but there are other elements that you need to consider as well. For example: Is your language clear and unambiguous, and is your topic relevant and interesting? 

Checklist for the problem statement

Checklist for the problem statement .

Use the points in the checklist below to assure the quality of your problem statement. Tick off each of the points that your problem statement complies with. Continue to work on your problem statement until it complies with most or all of the items on the list. This will help you make sure that your problem statement is satisfactory. 

The checklist has been prepared by the editorial team in collaboration with Susanne Højlund, associate professor at the School of Culture and Society - Department of Anthropology, Aarhus University. 

A hypothesis is a theoretical, hypothetical explanation that can be tested. It usually takes the form of a causal relationship or a causal explanation. You can also consider the hypothesis as a preliminary response to a research question or a problem statement. A hypothesis can be expressed in different ways, but generally, the following applies: 

The hypothesis is theoretical and builds on existing knowledge and general principles. 

The hypothesis can be tested through a study or an experiment. 

The hypothesis can either be confirmed or rejected. 

Testing a hypothesis

Your hypothesis can include a prediction of the results of your study based on a logical explanation. Your study will then show whether your hypothesis and your prediction appear to be correct or not. In other words, a good hypothesis is a hypothesis that you can test through a study or an experiment. 

A good hypothesis is theoretical and is based on existing knowledge, general principles and previous research within a similar academic problem area. It can also be a good idea to consider proposing several hypotheses. 

In science, it is generally believed that a hypothesis can turn out to be wrong, but that it can never be conclusively proven to be true. Consequently, your study or experiment should be designed so that it attempts to reject or falsify your hypothesis. If you fail to reject the hypothesis, it is more likely to be "correct". 

Inspiration from assignments by other students

Get a list of thesis titles from your field of study, and draw inspiration from other students’ problem statements. 

June 11, 2020 | How to's

Problem Statement vs Hypothesis: which ­­is more important for experimentation?

by Sadie Neve

When it comes to experimentation and conversion rate optimisation (CRO), we often see people relying too heavily on their instincts, abandoning logic and data in favour of their gut feelings. But really, nothing in experimentation is certain until tested. This realisation automatically makes you question everything you want to change about your website. This means experimentation should be approached like a scientific experiment that follows three core steps; identify a problem, form a hypothesis, and test that hypothesis.

But when it comes to experimentation, should you value the problem statement over the hypothesis? Or vice versa?

Which is more important: the problem statement or hypothesis?

At CreativeCX, we actually place equal importance on the problem statement and the hypothesis. This ensures that we consider both the customer problem that needs to be solved, as well as the business objectives.

All too often, we see companies either neglect the problem statement and hypothesis entirely or favour one over the other.

But weakness in either of these elements can seriously hinder the success of your experimentation programme.

So how can you structure both statements in such a way that you get the most out of your experiment?

The problem statement

First of all, what is the problem statement? A problem statement is a concise description of an issue that needs to be addressed or improved upon. In the case of digital products and services, this should be related to a problem that the customer has.

In any experiment, the problem statement should always come first. Without a problem, you have no real reason to conduct the experiment or understanding on what to conduct an experiment on.

The problem statement guides the strategic direction of your experiment while ensuring that you are always focusing on the customer.

How do we identify customer problems?

The data and research that you undertake will help you identify customer problems, either for your current customers or for your target audience. Identifying the pain points of your customer’s online behaviour should ideally come from multiple sources of data and research. This enables you to triangulate insights so that you can build a more complete picture of the problem, whilst also gaining an understanding of the magnitude of the issue. When starting your research process, you’ll probably find yourself having more questions than answers at the beginning. That’s fine; in fact, it’s normal at this early stage of the experiment.

Rather than letting this put you off, it is better to dig deeper, ask more questions and achieve a greater understanding of the customer problem before trying to find a solution. A greater understanding of the problem and how it’s affecting your customers will lead to better solutions and a higher win rate with your experiments. With this in mind, it is wise to collaborate with other teams within your business – preferably members of your CX and UX departments – who may be able to share relevant customer insights that they have discovered through their own research.

Once you have sufficient data, it is likely you will start to identify problem themes, which will help you understand the wider issues your customers are facing. This is where we start to create a clear problem statement.

How do you craft a clear problem statement?

A clear problem statement should help you identify what the problem is and the data that backs up your claim. At CreativeCX, we organise each problem statement as follows:

We believe [state the problem identified] because [state the supporting data].

Let’s demonstrate with an example. We work with an e-commerce company that sells women’s loungewear. Through our research, we discovered the following two pieces of data:

Usability testing showed users were moving back and forth between the product details page and the basket page to edit their selected size. Website data showed only 2% of customers engage with the “size guide” text link on the product details page. Based on this analysis, we have inferred a problem: users are struggling to understand which size they should choose. Through this, we are able to make the following problem statement:

We believe that users are struggling to understand which size they should choose because our data shows that users are editing their selected size multiple times on the basket and product details page and only 2% of customers engage with the sizing guide.

Can you see how much better this statement is compared to the following:

We think we have an issue with users understanding which size would fit them best.

Here are our top three questions we suggest you keep in mind when writing a problem statement:

Is my problem statement focused on my customers? Is my problem statement clear and precise? What data do I have to back up this problem? As you can see in the examples above, our first example answers all three questions while the second statement falls short on questions two and three.

Whilst your problem statement identifies the problem you hope to solve, the hypothesis helps you decide on how you will try to solve it.

The hypothesis statement

The hypothesis: you’ve probably come across this word years ago in a science class, and its meaning remains the same even in this context. Essentially, the hypothesis statement is a prediction for what you think will happen if you take a certain type of action to resolve a problem.

The hypothesis usually identifies what is going to be changed and the action’s potential outcome, as well as why you think the change will have that particular result.

Creating a hypothesis is a key part of any quality experiment and shouldn’t be rushed. Rushing over this critical step could mean that you miss out on key actions or insights further down the line.

Similar to the problem statement, the hypothesis should be precisely constructed. Having a vague hypothesis may actually be a sign that your problem statement isn’t as clear as you originally thought. An unclear problem statement or hypothesis could, in turn, result in your proposed solutions not having the desired or expected results.

How do you write a clear hypothesis?

There are many ways to write a strong hypothesis. At CreativeCX, we structure ours using the following formula:

By [state experiment change], we believe [user behaviour change], solving [state problem]. We expect to see [expected results].

Now, some may say this will create a hypothesis that is too lengthy. However, this structure clearly incorporates three key elements of an experiment: the problem we are trying to solve, the specific execution, and the expected result. More importantly, it strikes a balance between focusing on the business goals you want to achieve and optimising your customers’ online experience.

Let’s go back to our previous example. There might be multiple solutions to solving this sizing problem, all of which would require a different hypothesis. However, our problem statement has allowed us to identify that we need to increase user awareness of the sizing guide on the product page.

We have identified this as a top priority, so our hypothesis would be as follows:

By increasing link prominence for the sizing guide, we believe more customers will interact with the link, solving sizing uncertainty. We expect to see an increase in customers engaging with the size guide, as well as an increase in customers progressing from the basket to checkout.

Again, whilst this is lengthy, it is also precise. It clearly defines the experiment’s aim with both the business and its customers in mind.

Compare this to the following:

Making the sizing guide link larger will improve our profits.

Here are our top three questions to bear in mind when you’re writing a hypothesis:

Is my hypothesis a statement or a testable question? Is it clear and precise? Is my hypothesis human-friendly and keeping the customer in mind? As you can see, whilst our first example considered all three questions, the second is relatively vague and doesn’t relate to the customer at all.

What do I do once I have written a problem statement and hypothesis?

With your concise problem statement and hypothesis, you should have a great foundation for your experiment. The next step looks at designing your experiment, not in terms of actual visual designs, but what solutions you will be testing in a hope to validate your hypothesis and gain as much learnings on your customers as possible.

Look out for our future blog around how best to design your experiments and be creative with your potential variations.

If you have any questions about topics that have been covered in this blog or you’d like help with your experimentation or CRO programme, please don’t hesitate to reach out to us.

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How to Write a Good Research Question (w/ Examples)

What is a Research Question?

A research question is the main question that your study sought or is seeking to answer. A clear research question guides your research paper or thesis and states exactly what you want to find out, giving your work a focus and objective. Learning  how to write a hypothesis or research question is the start to composing any thesis, dissertation, or research paper. It is also one of the most important sections of a research proposal . 

A good research question not only clarifies the writing in your study; it provides your readers with a clear focus and facilitates their understanding of your research topic, as well as outlining your study’s objectives. Before drafting the paper and receiving research paper editing (and usually before performing your study), you should write a concise statement of what this study intends to accomplish or reveal.

Research Question Writing Tips

Listed below are the important characteristics of a good research question:

A good research question should:

• Be clear and provide specific information so readers can easily understand the purpose.
• Be focused in its scope and narrow enough to be addressed in the space allowed by your paper
• Be relevant and concise and express your main ideas in as few words as possible, like a hypothesis.
• Be precise and complex enough that it does not simply answer a closed “yes or no” question, but requires an analysis of arguments and literature prior to its being considered acceptable. 
• Be arguable or testable so that answers to the research question are open to scrutiny and specific questions and counterarguments.

Some of these characteristics might be difficult to understand in the form of a list. Let’s go into more detail about what a research question must do and look at some examples of research questions.

The research question should be specific and focused 

Research questions that are too broad are not suitable to be addressed in a single study. One reason for this can be if there are many factors or variables to consider. In addition, a sample data set that is too large or an experimental timeline that is too long may suggest that the research question is not focused enough.

A specific research question means that the collective data and observations come together to either confirm or deny the chosen hypothesis in a clear manner. If a research question is too vague, then the data might end up creating an alternate research problem or hypothesis that you haven’t addressed in your Introduction section .

The research question should be based on the literature 

An effective research question should be answerable and verifiable based on prior research because an effective scientific study must be placed in the context of a wider academic consensus. This means that conspiracy or fringe theories are not good research paper topics.

Instead, a good research question must extend, examine, and verify the context of your research field. It should fit naturally within the literature and be searchable by other research authors.

References to the literature can be in different citation styles and must be properly formatted according to the guidelines set forth by the publishing journal, university, or academic institution. This includes in-text citations as well as the Reference section . 

The research question should be realistic in time, scope, and budget

There are two main constraints to the research process: timeframe and budget.

A proper research question will include study or experimental procedures that can be executed within a feasible time frame, typically by a graduate doctoral or master’s student or lab technician. Research that requires future technology, expensive resources, or follow-up procedures is problematic.

A researcher’s budget is also a major constraint to performing timely research. Research at many large universities or institutions is publicly funded and is thus accountable to funding restrictions. 

The research question should be in-depth

Research papers, dissertations and theses , and academic journal articles are usually dozens if not hundreds of pages in length.

A good research question or thesis statement must be sufficiently complex to warrant such a length, as it must stand up to the scrutiny of peer review and be reproducible by other scientists and researchers.

Research Question Types

Qualitative and quantitative research are the two major types of research, and it is essential to develop research questions for each type of study. 

Quantitative Research Questions

Quantitative research questions are specific. A typical research question involves the population to be studied, dependent and independent variables, and the research design.

In addition, quantitative research questions connect the research question and the research design. In addition, it is not possible to answer these questions definitively with a “yes” or “no” response. For example, scientific fields such as biology, physics, and chemistry often deal with “states,” in which different quantities, amounts, or velocities drastically alter the relevance of the research.

As a consequence, quantitative research questions do not contain qualitative, categorical, or ordinal qualifiers such as “is,” “are,” “does,” or “does not.”

Categories of quantitative research questions

Qualitative research questions.

In quantitative research, research questions have the potential to relate to broad research areas as well as more specific areas of study. Qualitative research questions are less directional, more flexible, and adaptable compared with their quantitative counterparts. Thus, studies based on these questions tend to focus on “discovering,” “explaining,” “elucidating,” and “exploring.”

Categories of qualitative research questions

Quantitative and qualitative research question examples.

Good and Bad Research Question Examples

Below are some good (and not-so-good) examples of research questions that researchers can use to guide them in crafting their own research questions.

Research Question Example 1

The first research question is too vague in both its independent and dependent variables. There is no specific information on what “exposure” means. Does this refer to comments, likes, engagement, or just how much time is spent on the social media platform?

Second, there is no useful information on what exactly “affected” means. Does the subject’s behavior change in some measurable way? Or does this term refer to another factor such as the user’s emotions?

Research Question Example 2

In this research question, the first example is too simple and not sufficiently complex, making it difficult to assess whether the study answered the question. The author could really only answer this question with a simple “yes” or “no.” Further, the presence of data would not help answer this question more deeply, which is a sure sign of a poorly constructed research topic.

The second research question is specific, complex, and empirically verifiable. One can measure program effectiveness based on metrics such as attendance or grades. Further, “bullying” is made into an empirical, quantitative measurement in the form of recorded disciplinary actions.

Steps for Writing a Research Question

Good research questions are relevant, focused, and meaningful. It can be difficult to come up with a good research question, but there are a few steps you can follow to make it a bit easier.

1. Start with an interesting and relevant topic

Choose a research topic that is interesting but also relevant and aligned with your own country’s culture or your university’s capabilities. Popular academic topics include healthcare and medical-related research. However, if you are attending an engineering school or humanities program, you should obviously choose a research question that pertains to your specific study and major.

Below is an embedded graph of the most popular research fields of study based on publication output according to region. As you can see, healthcare and the basic sciences receive the most funding and earn the highest number of publications. 

2. Do preliminary research  

You can begin doing preliminary research once you have chosen a research topic. Two objectives should be accomplished during this first phase of research. First, you should undertake a preliminary review of related literature to discover issues that scholars and peers are currently discussing. With this method, you show that you are informed about the latest developments in the field.

Secondly, identify knowledge gaps or limitations in your topic by conducting a preliminary literature review . It is possible to later use these gaps to focus your research question after a certain amount of fine-tuning.

3. Narrow your research to determine specific research questions

You can focus on a more specific area of study once you have a good handle on the topic you want to explore. Focusing on recent literature or knowledge gaps is one good option. 

By identifying study limitations in the literature and overlooked areas of study, an author can carve out a good research question. The same is true for choosing research questions that extend or complement existing literature.

4. Evaluate your research question

Make sure you evaluate the research question by asking the following questions:

Is my research question clear?

The resulting data and observations that your study produces should be clear. For quantitative studies, data must be empirical and measurable. For qualitative, the observations should be clearly delineable across categories.

Is my research question focused and specific?

A strong research question should be specific enough that your methodology or testing procedure produces an objective result, not one left to subjective interpretation. Open-ended research questions or those relating to general topics can create ambiguous connections between the results and the aims of the study. 

Is my research question sufficiently complex?

The result of your research should be consequential and substantial (and fall sufficiently within the context of your field) to warrant an academic study. Simply reinforcing or supporting a scientific consensus is superfluous and will likely not be well received by most journal editors.  

Editing Your Research Question

Your research question should be fully formulated well before you begin drafting your research paper. However, you can receive English paper editing and proofreading services at any point in the drafting process. Language editors with expertise in your academic field can assist you with the content and language in your Introduction section or other manuscript sections. And if you need further assistance or information regarding paper compositions, in the meantime, check out our academic resources , which provide dozens of articles and videos on a variety of academic writing and publication topics.

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).

Essential 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 an effective 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

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

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