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What is the Correct Way to Write a Hypothesis?

Writing a hypothesis is a crucial step in the scientific method. It helps guide your research and provides a clear focus for your study. A well-crafted hypothesis predicts an outcome based on certain variables and sets the stage for testing and analysis. This article will walk you through the correct way to write a hypothesis, from understanding its importance to avoiding common mistakes.

Key Takeaways

• A hypothesis is a prediction that can be tested through scientific research.
• There are different types of hypotheses, including simple, complex, and null hypotheses.
• A good hypothesis should be clear, precise, and testable.
• Common pitfalls in hypothesis writing include subjectivity, complexity, and lack of testability.
• Testing and refining your hypothesis is an ongoing process that may require adjustments based on new data.

Understanding the Concept of a Hypothesis

Definition and importance.

A hypothesis is a proposed explanation for a phenomenon, serving as a starting point for further investigation. It is a testable statement predicting the outcome of a study. Hypotheses are crucial because they provide direction and focus for research, ensuring that studies are clear and grounded in existing knowledge.

Types of Hypotheses

There are several types of hypotheses, including:

• Null Hypothesis (H0): Suggests no relationship between variables.
• Alternative Hypothesis (H1): Indicates a relationship between variables.
• Directional Hypothesis: Predicts the direction of the relationship.
• Non-Directional Hypothesis: Does not predict the direction, only that a relationship exists.

Role in Scientific Research

In scientific research, hypotheses play a vital role. They help in formulating research questions and guide the design of experiments. By providing a clear focus, hypotheses ensure that research is systematic and that the findings are reliable and valid. This structured approach enhances the credibility and reliability of the research outcomes.

Steps to Formulate a Hypothesis

Identifying research questions.

The first step in formulating a hypothesis is to identify the research questions you aim to answer. These questions should be specific and focused, guiding your investigation. A well-defined research question sets the stage for a clear and testable hypothesis. Consider what you want to discover and why it matters. This will help you narrow down your focus and make your hypothesis more precise.

Conducting Preliminary Research

Before you can write a hypothesis, you need to conduct preliminary research. This involves gathering information from various sources to understand the current state of knowledge on your topic. Look for gaps in the existing research that your study could fill. Preliminary research helps you refine your research questions and provides a foundation for your hypothesis. Targeted research is crucial for formulating a hypothesis that can advance scientific understanding.

Formulating the Hypothesis Statement

Once you have a clear research question and have conducted preliminary research, you can formulate your hypothesis statement. This statement should be concise and specific, outlining the expected relationship between variables. A good hypothesis is testable and falsifiable, meaning it can be supported or refuted through experimentation. Think of your hypothesis as a tentative answer to your research question, one that you will test through your study.

Characteristics of a Well-Written Hypothesis

Clarity and precision.

A well-written hypothesis must be clear and precise. This means avoiding vague language and ensuring that the hypothesis is easy to understand. Clarity is crucial because it helps others understand exactly what you are testing. For instance, instead of saying "plants grow better," specify "plants grow taller when given fertilizer." This precision helps in demystifying the concept of a thesis statement .

Testability

Your hypothesis should be testable, meaning it can be supported or refuted through experimentation or observation. A testable hypothesis allows you to design experiments that can confirm or deny your predictions. For example, you might hypothesize that "students who sleep 8 hours perform better on tests than those who sleep less." This makes it easier to conduct a study and gather data.

Variables and Relationships

A good hypothesis clearly defines the variables and the relationship between them. Typically, this involves an independent variable (what you change) and a dependent variable (what you measure). For example, "If the amount of sunlight is increased, then the growth rate of the plant will increase." This if-then structure helps in crafting a bachelor thesis by clearly outlining what is being tested and what the expected outcome is.

Common Pitfalls in Hypothesis Writing

When writing a hypothesis, it's easy to make mistakes that can undermine your research. Here are some common pitfalls to avoid:

Subjectivity and Bias

A hypothesis should be objective and free from personal bias. If you let your own opinions influence your hypothesis, it can skew your research results. Always aim for neutrality to ensure your findings are valid.

Overly Complex Statements

Keep your hypothesis simple and clear. Overly complex statements can confuse readers and make your research harder to follow. If your hypothesis is too complicated, break it down into smaller, more manageable parts.

Lack of Testability

A hypothesis must be testable. If you can't test your hypothesis through experiments or observations, it's not useful for scientific research. Make sure your hypothesis can be supported or refuted by data.

Facing the unexpected: dealing with data that contradicts your hypothesis. Consider limitations, revise hypothesis, adjust methodology, and interpret findings when faced with contradictory data.

Examples of Effective Hypotheses

When crafting a hypothesis, it's helpful to look at examples to understand what makes them effective. Here are some examples to guide you.

Simple Hypothesis Examples

A simple hypothesis predicts a relationship between two variables. For instance, "Plants grow better with bottled water than tap water." This hypothesis is straightforward and easy to test.

Complex Hypothesis Examples

A complex hypothesis involves multiple variables. An example could be, "Children who play first-person shooter games will show higher levels of aggression than children who do not." This hypothesis considers both the type of game and the level of aggression.

Null Hypothesis Examples

A null hypothesis states that there is no relationship between the variables. For example, "There is no difference in memory performance between adults and children." This type of hypothesis is essential for statistical testing.

Understanding these examples can help you formulate your own hypotheses more effectively. Remember, a good hypothesis should be clear, testable, and directly related to your research question .

Testing and Validating Your Hypothesis

Designing experiments.

To test your hypothesis, you need to design a solid experiment. Start by identifying your independent and dependent variables. Make sure your experiment is controlled, meaning you only change one variable at a time. This helps you see the direct effects of that variable. A well-designed experiment is crucial for reliable results.

Data Collection Methods

Collecting data accurately is key to validating your hypothesis. Use methods like surveys, observations, or experiments to gather data. Ensure your data collection process is consistent and unbiased. This will help you draw meaningful conclusions from your data.

Analyzing Results

Once you have your data, it's time to analyze it. Use statistical tools to interpret your data and see if it supports your hypothesis. Look for patterns and relationships between variables. Understanding and applying key stats in experimental research is essential for drawing valid conclusions. This step is vital in the process of statistical storytelling .

Revising and Refining Your Hypothesis

Incorporating feedback.

When revising your hypothesis, it's crucial to consider feedback from peers, mentors, or advisors. This stage involves analyzing what ideas can be combined , what should be kept separate, and drawing inferences. Feedback can highlight areas of your hypothesis that need more clarity or precision.

Adjusting for New Data

As you gather more data, you might find that your original hypothesis needs tweaking. This is a normal part of the research process. Be open to modifying your hypothesis to better align with the new information you have collected. This ensures that your hypothesis remains relevant and testable.

Ensuring Alignment with Research Goals

Your hypothesis should always align with your overall research goals. Regularly revisiting your research questions and objectives can help you ensure that your hypothesis is still on track. If your research goals evolve, your hypothesis should be adjusted accordingly to maintain coherence in your study.

When you revisit and refine your hypothesis, you pave the way for a stronger thesis. It's a crucial step that can make a big difference in your research. If you're feeling stuck or unsure about how to proceed, don't worry. Our Thesis Action Plan is here to guide you through every step. Visit our website to learn more and take the first step towards a stress-free thesis journey.

In summary, writing a hypothesis is a crucial step in the scientific method that requires careful planning and clear thinking. By understanding the basics, such as ensuring your hypothesis is testable and based on research, you can set a strong foundation for your study. Remember, a well-crafted hypothesis not only guides your research but also helps in drawing meaningful conclusions. As you continue to practice and refine your skills, you'll find that writing hypotheses becomes more intuitive and integral to your scientific inquiries.

Frequently Asked Questions

What is a hypothesis.

A hypothesis is a statement that predicts the outcome of your research. It's like an educated guess about what you think will happen.

Why is a hypothesis important in scientific research?

A hypothesis helps guide your research. It gives you a clear focus and direction for your experiments or studies.

What are the different types of hypotheses?

There are several types, including simple, complex, and null hypotheses. Each type serves a different purpose in research.

How do I write a clear and precise hypothesis?

Make sure your hypothesis is specific and easy to understand. Avoid using vague terms and be as detailed as possible.

What makes a hypothesis testable?

A testable hypothesis can be supported or refuted through experiments or observations. It should be measurable and clear.

What are common mistakes to avoid when writing a hypothesis?

Avoid being subjective or biased, making overly complex statements, and writing hypotheses that can't be tested.

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How to Write a Research Hypothesis: Good & Bad Examples

What is a research hypothesis?

A research hypothesis is an attempt at explaining a phenomenon or the relationships between phenomena/variables in the real world. Hypotheses are sometimes called “educated guesses”, but they are in fact (or let’s say they should be) based on previous observations, existing theories, scientific evidence, and logic. A research hypothesis is also not a prediction—rather, predictions are ( should be) based on clearly formulated hypotheses. For example, “We tested the hypothesis that KLF2 knockout mice would show deficiencies in heart development” is an assumption or prediction, not a hypothesis. 

The research hypothesis at the basis of this prediction is “the product of the KLF2 gene is involved in the development of the cardiovascular system in mice”—and this hypothesis is probably (hopefully) based on a clear observation, such as that mice with low levels of Kruppel-like factor 2 (which KLF2 codes for) seem to have heart problems. From this hypothesis, you can derive the idea that a mouse in which this particular gene does not function cannot develop a normal cardiovascular system, and then make the prediction that we started with. 

What is the difference between a hypothesis and a prediction?

You might think that these are very subtle differences, and you will certainly come across many publications that do not contain an actual hypothesis or do not make these distinctions correctly. But considering that the formulation and testing of hypotheses is an integral part of the scientific method, it is good to be aware of the concepts underlying this approach. The two hallmarks of a scientific hypothesis are falsifiability (an evaluation standard that was introduced by the philosopher of science Karl Popper in 1934) and testability —if you cannot use experiments or data to decide whether an idea is true or false, then it is not a hypothesis (or at least a very bad one).

So, in a nutshell, you (1) look at existing evidence/theories, (2) come up with a hypothesis, (3) make a prediction that allows you to (4) design an experiment or data analysis to test it, and (5) come to a conclusion. Of course, not all studies have hypotheses (there is also exploratory or hypothesis-generating research), and you do not necessarily have to state your hypothesis as such in your paper. 

But for the sake of understanding the principles of the scientific method, let’s first take a closer look at the different types of hypotheses that research articles refer to and then give you a step-by-step guide for how to formulate a strong hypothesis for your own paper.

Types of Research Hypotheses

Hypotheses can be simple , which means they describe the relationship between one single independent variable (the one you observe variations in or plan to manipulate) and one single dependent variable (the one you expect to be affected by the variations/manipulation). If there are more variables on either side, you are dealing with a complex hypothesis. You can also distinguish hypotheses according to the kind of relationship between the variables you are interested in (e.g., causal or associative ). But apart from these variations, we are usually interested in what is called the “alternative hypothesis” and, in contrast to that, the “null hypothesis”. If you think these two should be listed the other way round, then you are right, logically speaking—the alternative should surely come second. However, since this is the hypothesis we (as researchers) are usually interested in, let’s start from there.

Alternative Hypothesis

If you predict a relationship between two variables in your study, then the research hypothesis that you formulate to describe that relationship is your alternative hypothesis (usually H1 in statistical terms). The goal of your hypothesis testing is thus to demonstrate that there is sufficient evidence that supports the alternative hypothesis, rather than evidence for the possibility that there is no such relationship. The alternative hypothesis is usually the research hypothesis of a study and is based on the literature, previous observations, and widely known theories. 

Null Hypothesis

The hypothesis that describes the other possible outcome, that is, that your variables are not related, is the null hypothesis ( H0 ). Based on your findings, you choose between the two hypotheses—usually that means that if your prediction was correct, you reject the null hypothesis and accept the alternative. Make sure, however, that you are not getting lost at this step of the thinking process: If your prediction is that there will be no difference or change, then you are trying to find support for the null hypothesis and reject H1. 

Directional Hypothesis

While the null hypothesis is obviously “static”, the alternative hypothesis can specify a direction for the observed relationship between variables—for example, that mice with higher expression levels of a certain protein are more active than those with lower levels. This is then called a one-tailed hypothesis. 

Another example for a directional one-tailed alternative hypothesis would be that 

H1: Attending private classes before important exams has a positive effect on performance. 

Your null hypothesis would then be that

H0: Attending private classes before important exams has no/a negative effect on performance.

Nondirectional Hypothesis

A nondirectional hypothesis does not specify the direction of the potentially observed effect, only that there is a relationship between the studied variables—this is called a two-tailed hypothesis. For instance, if you are studying a new drug that has shown some effects on pathways involved in a certain condition (e.g., anxiety) in vitro in the lab, but you can’t say for sure whether it will have the same effects in an animal model or maybe induce other/side effects that you can’t predict and potentially increase anxiety levels instead, you could state the two hypotheses like this:

H1: The only lab-tested drug (somehow) affects anxiety levels in an anxiety mouse model.

You then test this nondirectional alternative hypothesis against the null hypothesis:

H0: The only lab-tested drug has no effect on anxiety levels in an anxiety mouse model.

How to Write a Hypothesis for a Research Paper

Now that we understand the important distinctions between different kinds of research hypotheses, let’s look at a simple process of how to write a hypothesis.

Writing a Hypothesis Step:1

Ask a question, based on earlier research. Research always starts with a question, but one that takes into account what is already known about a topic or phenomenon. For example, if you are interested in whether people who have pets are happier than those who don’t, do a literature search and find out what has already been demonstrated. You will probably realize that yes, there is quite a bit of research that shows a relationship between happiness and owning a pet—and even studies that show that owning a dog is more beneficial than owning a cat ! Let’s say you are so intrigued by this finding that you wonder: 

What is it that makes dog owners even happier than cat owners? 

Let’s move on to Step 2 and find an answer to that question.

Writing a Hypothesis Step 2:

Formulate a strong hypothesis by answering your own question. Again, you don’t want to make things up, take unicorns into account, or repeat/ignore what has already been done. Looking at the dog-vs-cat papers your literature search returned, you see that most studies are based on self-report questionnaires on personality traits, mental health, and life satisfaction. What you don’t find is any data on actual (mental or physical) health measures, and no experiments. You therefore decide to make a bold claim come up with the carefully thought-through hypothesis that it’s maybe the lifestyle of the dog owners, which includes walking their dog several times per day, engaging in fun and healthy activities such as agility competitions, and taking them on trips, that gives them that extra boost in happiness. You could therefore answer your question in the following way:

Dog owners are happier than cat owners because of the dog-related activities they engage in.

Now you have to verify that your hypothesis fulfills the two requirements we introduced at the beginning of this resource article: falsifiability and testability . If it can’t be wrong and can’t be tested, it’s not a hypothesis. We are lucky, however, because yes, we can test whether owning a dog but not engaging in any of those activities leads to lower levels of happiness or well-being than owning a dog and playing and running around with them or taking them on trips.  

Writing a Hypothesis Step 3:

Make your predictions and define your variables. We have verified that we can test our hypothesis, but now we have to define all the relevant variables, design our experiment or data analysis, and make precise predictions. You could, for example, decide to study dog owners (not surprising at this point), let them fill in questionnaires about their lifestyle as well as their life satisfaction (as other studies did), and then compare two groups of active and inactive dog owners. Alternatively, if you want to go beyond the data that earlier studies produced and analyzed and directly manipulate the activity level of your dog owners to study the effect of that manipulation, you could invite them to your lab, select groups of participants with similar lifestyles, make them change their lifestyle (e.g., couch potato dog owners start agility classes, very active ones have to refrain from any fun activities for a certain period of time) and assess their happiness levels before and after the intervention. In both cases, your independent variable would be “ level of engagement in fun activities with dog” and your dependent variable would be happiness or well-being . 

Examples of a Good and Bad Hypothesis

Let’s look at a few examples of good and bad hypotheses to get you started.

Good Hypothesis Examples

Bad Hypothesis Examples

Tips for Writing a Research Hypothesis

If you understood the distinction between a hypothesis and a prediction we made at the beginning of this article, then you will have no problem formulating your hypotheses and predictions correctly. To refresh your memory: We have to (1) look at existing evidence, (2) come up with a hypothesis, (3) make a prediction, and (4) design an experiment. For example, you could summarize your dog/happiness study like this:

(1) While research suggests that dog owners are happier than cat owners, there are no reports on what factors drive this difference. (2) We hypothesized that it is the fun activities that many dog owners (but very few cat owners) engage in with their pets that increases their happiness levels. (3) We thus predicted that preventing very active dog owners from engaging in such activities for some time and making very inactive dog owners take up such activities would lead to an increase and decrease in their overall self-ratings of happiness, respectively. (4) To test this, we invited dog owners into our lab, assessed their mental and emotional well-being through questionnaires, and then assigned them to an “active” and an “inactive” group, depending on… 

Note that you use “we hypothesize” only for your hypothesis, not for your experimental prediction, and “would” or “if – then” only for your prediction, not your hypothesis. A hypothesis that states that something “would” affect something else sounds as if you don’t have enough confidence to make a clear statement—in which case you can’t expect your readers to believe in your research either. Write in the present tense, don’t use modal verbs that express varying degrees of certainty (such as may, might, or could ), and remember that you are not drawing a conclusion while trying not to exaggerate but making a clear statement that you then, in a way, try to disprove . And if that happens, that is not something to fear but an important part of the scientific process.

Similarly, don’t use “we hypothesize” when you explain the implications of your research or make predictions in the conclusion section of your manuscript, since these are clearly not hypotheses in the true sense of the word. As we said earlier, you will find that many authors of academic articles do not seem to care too much about these rather subtle distinctions, but thinking very clearly about your own research will not only help you write better but also ensure that even that infamous Reviewer 2 will find fewer reasons to nitpick about your manuscript. 

Perfect Your Manuscript With Professional Editing

Now that you know how to write a strong research hypothesis for your research paper, you might be interested in our free AI Proofreader , Wordvice AI, which finds and fixes errors in grammar, punctuation, and word choice in academic texts. Or if you are interested in human proofreading , check out our English editing services , including research paper editing and manuscript editing .

On the Wordvice academic resources website , you can also find many more articles and other resources that can help you with writing the other parts of your research paper , with making a research paper outline before you put everything together, or with writing an effective cover letter once you are ready to submit.

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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.

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How to Write a Hypothesis? Types and Examples 

All research studies involve the use of the scientific method, which is a mathematical and experimental technique used to conduct experiments by developing and testing a hypothesis or a prediction about an outcome. Simply put, a hypothesis is a suggested solution to a problem. It includes elements that are expressed in terms of relationships with each other to explain a condition or an assumption that hasn’t been verified using facts. 1 The typical steps in a scientific method include developing such a hypothesis, testing it through various methods, and then modifying it based on the outcomes of the experiments.  

A research hypothesis can be defined as a specific, testable prediction about the anticipated results of a study. 2 Hypotheses help guide the research process and supplement the aim of the study. After several rounds of testing, hypotheses can help develop scientific theories. 3 Hypotheses are often written as if-then statements. 

Here are two hypothesis examples: 

Dandelions growing in nitrogen-rich soils for two weeks develop larger leaves than those in nitrogen-poor soils because nitrogen stimulates vegetative growth. 4  

If a company offers flexible work hours, then their employees will be happier at work. 5  

Table of Contents

• What is a hypothesis? 
• Types of hypotheses 
• Characteristics of a hypothesis 
• Functions of a hypothesis 
• How to write a hypothesis 
• Hypothesis examples 
• Frequently asked questions 

What is a hypothesis?

A hypothesis expresses an expected relationship between variables in a study and is developed before conducting any research. Hypotheses are not opinions but rather are expected relationships based on facts and observations. They help support scientific research and expand existing knowledge. An incorrectly formulated hypothesis can affect the entire experiment leading to errors in the results so it’s important to know how to formulate a hypothesis and develop it carefully.

A few sources of a hypothesis include observations from prior studies, current research and experiences, competitors, scientific theories, and general conditions that can influence people. Figure 1 depicts the different steps in a research design and shows where exactly in the process a hypothesis is developed. 4  

There are seven different types of hypotheses—simple, complex, directional, nondirectional, associative and causal, null, and alternative. 

Types of hypotheses

The seven types of hypotheses are listed below: 5 , 6,7  

• Simple : Predicts the relationship between a single dependent variable and a single independent variable. 

Example: Exercising in the morning every day will increase your productivity.  

• Complex : Predicts the relationship between two or more variables. 

Example: Spending three hours or more on social media daily will negatively affect children’s mental health and productivity, more than that of adults.  

• Directional : Specifies the expected direction to be followed and uses terms like increase, decrease, positive, negative, more, or less. 

Example: The inclusion of intervention X decreases infant mortality compared to the original treatment.  

• Non-directional : Does not predict the exact direction, nature, or magnitude of the relationship between two variables but rather states the existence of a relationship. This hypothesis may be used when there is no underlying theory or if findings contradict prior research. 

Example: Cats and dogs differ in the amount of affection they express.  

• Associative and causal : An associative hypothesis suggests an interdependency between variables, that is, how a change in one variable changes the other.  

Example: There is a positive association between physical activity levels and overall health.  

A causal hypothesis, on the other hand, expresses a cause-and-effect association between variables. 

Example: Long-term alcohol use causes liver damage.  

• Null : Claims that the original hypothesis is false by showing that there is no relationship between the variables. 

Example: Sleep duration does not have any effect on productivity.  

• Alternative : States the opposite of the null hypothesis, that is, a relationship exists between two variables. 

Example: Sleep duration affects productivity.  

Characteristics of a hypothesis

So, what makes a good hypothesis? Here are some important characteristics of a hypothesis. 8,9  

• Testable : You must be able to test the hypothesis using scientific methods to either accept or reject the prediction. 
• Falsifiable : It should be possible to collect data that reject rather than support the hypothesis. 
• Logical : Hypotheses shouldn’t be a random guess but rather should be based on previous theories, observations, prior research, and logical reasoning. 
• Positive : The hypothesis statement about the existence of an association should be positive, that is, it should not suggest that an association does not exist. Therefore, the language used and knowing how to phrase a hypothesis is very important. 
• Clear and accurate : The language used should be easily comprehensible and use correct terminology. 
• Relevant : The hypothesis should be relevant and specific to the research question. 
• Structure : Should include all the elements that make a good hypothesis: variables, relationship, and outcome. 

Functions of a hypothesis

The following list mentions some important functions of a hypothesis: 1  

• Maintains the direction and progress of the research. 
• Expresses the important assumptions underlying the proposition in a single statement. 
• Establishes a suitable context for researchers to begin their investigation and for readers who are referring to the final report. 
• Provides an explanation for the occurrence of a specific phenomenon. 
• Ensures selection of appropriate and accurate facts necessary and relevant to the research subject. 

To summarize, a hypothesis provides the conceptual elements that complete the known data, conceptual relationships that systematize unordered elements, and conceptual meanings and interpretations that explain the unknown phenomena. 1  

How to write a hypothesis

Listed below are the main steps explaining how to write a hypothesis. 2,4,5  

• Make an observation and identify variables : Observe the subject in question and try to recognize a pattern or a relationship between the variables involved. This step provides essential background information to begin your research.  

For example, if you notice that an office’s vending machine frequently runs out of a specific snack, you may predict that more people in the office choose that snack over another. 

• Identify the main research question : After identifying a subject and recognizing a pattern, the next step is to ask a question that your hypothesis will answer.  

For example, after observing employees’ break times at work, you could ask “why do more employees take breaks in the morning rather than in the afternoon?” 

• Conduct some preliminary research to ensure originality and novelty : Your initial answer, which is your hypothesis, to the question is based on some pre-existing information about the subject. However, to ensure that your hypothesis has not been asked before or that it has been asked but rejected by other researchers you would need to gather additional information.  

For example, based on your observations you might state a hypothesis that employees work more efficiently when the air conditioning in the office is set at a lower temperature. However, during your preliminary research you find that this hypothesis was proven incorrect by a prior study. 

• Develop a general statement : After your preliminary research has confirmed the originality of your proposed answer, draft a general statement that includes all variables, subjects, and predicted outcome. The statement could be if/then or declarative.  
• Finalize the hypothesis statement : Use the PICOT model, which clarifies how to word a hypothesis effectively, when finalizing the statement. This model lists the important components required to write a hypothesis. 

P opulation: The specific group or individual who is the main subject of the research 

I nterest: The main concern of the study/research question 

C omparison: The main alternative group 

O utcome: The expected results  

T ime: Duration of the experiment 

Once you’ve finalized your hypothesis statement you would need to conduct experiments to test whether the hypothesis is true or false. 

Hypothesis examples

The following table provides examples of different types of hypotheses. 10 ,11  

Key takeaways  

Here’s a summary of all the key points discussed in this article about how to write a hypothesis. 

• A hypothesis is an assumption about an association between variables made based on limited evidence, which should be tested. 
• A hypothesis has four parts—the research question, independent variable, dependent variable, and the proposed relationship between the variables.   
• The statement should be clear, concise, testable, logical, and falsifiable. 
• There are seven types of hypotheses—simple, complex, directional, non-directional, associative and causal, null, and alternative. 
• A hypothesis provides a focus and direction for the research to progress. 
• A hypothesis plays an important role in the scientific method by helping to create an appropriate experimental design. 

Frequently asked questions

Hypotheses and research questions have different objectives and structure. The following table lists some major differences between the two. 9  

Here are a few examples to differentiate between a research question and hypothesis. 

Yes, here’s a simple checklist to help you gauge the effectiveness of your hypothesis. 9   1. When writing a hypothesis statement, check if it:  2. Predicts the relationship between the stated variables and the expected outcome.  3. Uses simple and concise language and is not wordy.  4. Does not assume readers’ knowledge about the subject.  5. Has observable, falsifiable, and testable results. 

As mentioned earlier in this article, a hypothesis is an assumption or prediction about an association between variables based on observations and simple evidence. These statements are usually generic. Research objectives, on the other hand, are more specific and dictated by hypotheses. The same hypothesis can be tested using different methods and the research objectives could be different in each case.     For example, Louis Pasteur observed that food lasts longer at higher altitudes, reasoned that it could be because the air at higher altitudes is cleaner (with fewer or no germs), and tested the hypothesis by exposing food to air cleaned in the laboratory. 12 Thus, a hypothesis is predictive—if the reasoning is correct, X will lead to Y—and research objectives are developed to test these predictions. 

Null hypothesis testing is a method to decide between two assumptions or predictions between variables (null and alternative hypotheses) in a statistical relationship in a sample. The null hypothesis, denoted as H 0 , claims that no relationship exists between variables in a population and any relationship in the sample reflects a sampling error or occurrence by chance. The alternative hypothesis, denoted as H 1 , claims that there is a relationship in the population. In every study, researchers need to decide whether the relationship in a sample occurred by chance or reflects a relationship in the population. This is done by hypothesis testing using the following steps: 13   1. Assume that the null hypothesis is true.  2. Determine how likely the sample relationship would be if the null hypothesis were true. This probability is called the p value.  3. If the sample relationship would be extremely unlikely, reject the null hypothesis and accept the alternative hypothesis. If the relationship would not be unlikely, accept the null hypothesis. 

To summarize, researchers should know how to write a good hypothesis to ensure that their research progresses in the required direction. A hypothesis is a testable prediction about any behavior or relationship between variables, usually based on facts and observation, and states an expected outcome.  

We hope this article has provided you with essential insight into the different types of hypotheses and their functions so that you can use them appropriately in your next research project. 

References  

• Dalen, DVV. The function of hypotheses in research. Proquest website. Accessed April 8, 2024. https://www.proquest.com/docview/1437933010?pq-origsite=gscholar&fromopenview=true&sourcetype=Scholarly%20Journals&imgSeq=1  
• McLeod S. Research hypothesis in psychology: Types & examples. SimplyPsychology website. Updated December 13, 2023. Accessed April 9, 2024. https://www.simplypsychology.org/what-is-a-hypotheses.html  
• Scientific method. Britannica website. Updated March 14, 2024. Accessed April 9, 2024. https://www.britannica.com/science/scientific-method  
• The hypothesis in science writing. Accessed April 10, 2024. https://berks.psu.edu/sites/berks/files/campus/HypothesisHandout_Final.pdf  
• How to develop a hypothesis (with elements, types, and examples). Indeed.com website. Updated February 3, 2023. Accessed April 10, 2024. https://www.indeed.com/career-advice/career-development/how-to-write-a-hypothesis  
• Types of research hypotheses. Excelsior online writing lab. Accessed April 11, 2024. https://owl.excelsior.edu/research/research-hypotheses/types-of-research-hypotheses/  
• What is a research hypothesis: how to write it, types, and examples. Researcher.life website. Published February 8, 2023. Accessed April 11, 2024. https://researcher.life/blog/article/how-to-write-a-research-hypothesis-definition-types-examples/  
• Developing a hypothesis. Pressbooks website. Accessed April 12, 2024. https://opentext.wsu.edu/carriecuttler/chapter/developing-a-hypothesis/  
• What is and how to write a good hypothesis in research. Elsevier author services website. Accessed April 12, 2024. https://scientific-publishing.webshop.elsevier.com/manuscript-preparation/what-how-write-good-hypothesis-research/  
• How to write a great hypothesis. Verywellmind website. Updated March 12, 2023. Accessed April 13, 2024. https://www.verywellmind.com/what-is-a-hypothesis-2795239  
• 15 Hypothesis examples. Helpfulprofessor.com Published September 8, 2023. Accessed March 14, 2024. https://helpfulprofessor.com/hypothesis-examples/ 
• Editage insights. What is the interconnectivity between research objectives and hypothesis? Published February 24, 2021. Accessed April 13, 2024. https://www.editage.com/insights/what-is-the-interconnectivity-between-research-objectives-and-hypothesis  
• Understanding null hypothesis testing. BCCampus open publishing. Accessed April 16, 2024. https://opentextbc.ca/researchmethods/chapter/understanding-null-hypothesis-testing/#:~:text=In%20null%20hypothesis%20testing%2C%20this,said%20to%20be%20statistically%20significant  

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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.

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• 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 .

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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.

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How to Write a Hypothesis [31 Tips + Examples]

Writing hypotheses can seem tricky, but it’s essential for a solid scientific inquiry.

Here is a quick summary of how to write a hypothesis:

Write a hypothesis by clearly defining your research question, identifying independent and dependent variables, formulating a measurable prediction, and ensuring it can be tested through experimentation. Include an “if…then” statement for clarity.

I’ve crafted dozens in my research, from basic biology experiments to business marketing strategies.

Let me walk you through how to write a solid hypothesis, step by step.

Writing a Hypothesis: The Basics

Table of Contents

A hypothesis is a statement predicting the relationship between variables based on observations and existing knowledge. To craft a good hypothesis:

• Identify variables – Determine the independent and dependent variables involved.
• Predict relationships – Predict the interaction between these variables.
• Test the statement – Ensure the hypothesis is testable and falsifiable.

A solid hypothesis guides your research and sets the foundation for your experiment.

31 Tips for Writing a Hypothesis

There are at least 31 tips to write a good hypothesis.

Keep reading to learn every tip plus three examples to make sure that you can instantly apply it to your writing.

Tip 1: Start with a Clear Research Question

A clear research question ensures your hypothesis is targeted.

• Identify the broad topic you’re curious about, then refine it to a specific question.
• Use guiding questions like “What impact does variable X have on variable Y?”
• How does fertilizer affect plant growth?
• Does social media influence mental health in teens?
• Can personalized ads increase customer engagement?

Tip 2: Do Background Research

Research helps you understand current knowledge and any existing gaps.

• Review scholarly articles, reputable websites, and textbooks.
• Focus on understanding the relationships between variables in existing research.
• Academic journals like ScienceDirect or JSTOR.
• Google Scholar.
• Reputable news articles.

Tip 3: Identify Independent and Dependent Variables

The independent variable is what you change or control. The dependent variable is what you measure.

• Clearly define these variables to make your hypothesis precise.
• Think of different factors that could be influencing your dependent variable.
• Type of fertilizer (independent) and plant growth (dependent).
• Amount of screen time (independent) and anxiety levels (dependent).
• Marketing strategies (independent) and customer engagement (dependent).

Tip 4: Make Your Hypothesis Testable

A hypothesis must be measurable and falsifiable.

• Ensure your hypothesis can be supported or refuted through data collection.
• Include numerical variables or qualitative changes to ensure measurability.
• “Increasing screen time will increase anxiety levels in teenagers.”
• “Using fertilizer X will yield higher crop productivity.”
• “A/B testing marketing strategies will show higher engagement with personalized ads.”

Tip 5: Be Specific and Concise

Keep your hypothesis straightforward and to the point.

• Avoid vague terms that could mislead or cause confusion.
• Clearly outline what you’re measuring and how the variables interact.
• “Replacing chemical fertilizers with organic ones will result in slower plant growth.”
• “A social media break will decrease anxiety in high school students.”
• “Ads targeting user preferences will boost click-through rates by 10%.”

Tip 6: Choose Simple Language

Use simple, understandable language to ensure clarity.

• Avoid jargon and overly complex terms that could confuse readers.
• Make the hypothesis comprehensible to non-experts in the field.
• “Organic fertilizer will reduce plant growth.”
• “High schoolers will feel less anxious after a social media detox.”
• “Targeted ads will increase customer engagement.”

Tip 7: Formulate a Null Hypothesis

A null hypothesis assumes no relationship between variables.

• Create a counterpoint to your main hypothesis, asserting that there is no effect.
• This allows you to compare results directly and identify statistical significance.
• “Fertilizer type will not affect plant growth.”
• “Social media use will not influence anxiety.”
• “Targeted ads will not affect customer engagement.”

Tip 8: State Alternative Hypotheses

Provide alternative hypotheses to explore other plausible relationships.

• They offer a contingency plan if your primary hypothesis is not supported.
• These should still align with your research question and measurable variables.
• “Fertilizer X will only affect plant growth if used in specific soil types.”
• “Social media might impact anxiety only in certain age groups.”
• “Customer engagement might only improve with highly personalized ads.”

Tip 9: Use “If…Then” Statements

“If…then” statements simplify the cause-and-effect structure.

• The “if” clause identifies the independent variable, while “then” identifies the dependent.
• It makes your hypothesis easier to understand and directly testable.
• “If plants receive organic fertilizer, then their growth rate will slow.”
• “If teens stop using social media, then their anxiety will decrease.”
• “If ads are personalized, then click-through rates will increase.”

Tip 10: Avoid Assumptions

Don’t assume the audience understands your variables or relationships.

• Clearly define terms and relationships to avoid misinterpretation.
• Provide background context where necessary for clarity.
• Define “anxiety” as a feeling of worry or unease.
• Specify “plant growth” as the height and health of plants.
• Describe “personalized ads” as ads matching user preferences.

Tip 11: Review Existing Literature

Previous research offers insights into forming a hypothesis.

• Conduct a thorough literature review to identify trends and gaps.
• Use these studies to refine and build upon your hypothesis.
• Studies showing a link between screen time and anxiety.
• Research on organic versus chemical fertilizers.
• Customer behavior analysis in different marketing channels.

Tip 12: Consider Multiple Variables

Hypotheses with multiple variables can offer deeper insights.

• Explore combinations of independent and dependent variables to see their relationships.
• Plan experiments accordingly to distinguish separate effects.
• Studying fertilizer type and soil composition effects on plant growth.
• Testing social media use frequency and content type on anxiety.
• Analyzing marketing strategies combined with product preferences.

Tip 13: Review Ethical Considerations

Ethics are essential for trustworthy research.

• Avoid hypotheses that could cause harm to participants or the environment.
• Seek approval from relevant ethical boards or committees.
• Avoiding experiments causing undue stress to teenagers.
• Preventing chemical contamination when testing fertilizers.
• Respecting privacy with personalized ads.

Tip 14: Test with Pilot Studies

Small-scale pilot studies test feasibility and refine hypotheses.

• Use them to identify potential issues and adjust before full-scale research.
• Ensure pilot tests align with ethical standards.
• Testing different fertilizer types on small plant samples.
• Trying brief social media breaks with a small group of teens.
• Conducting A/B tests on ad personalization with a subset of customers.

Tip 15: Build Hypotheses on Existing Theories

Existing theories provide strong foundations.

• Use established frameworks to develop or refine your hypothesis.
• Testing theoretical predictions can yield meaningful data.
• Applying agricultural theories on soil and crop management.
• Using psychology theories on screen addiction and mental health.
• Referencing marketing theories like consumer behavior analysis.

Tip 16: Address Real-World Problems

Solve real-world problems through practical hypotheses.

• Make sure your research question has relevant, impactful applications.
• Focus on everyday challenges where actionable insights can help.
• Testing new eco-friendly farming methods.
• Reducing anxiety by improving digital wellbeing.
• Improving marketing ROI with personalized strategies.

Tip 17: Aim for Clear, Measurable Outcomes

The results should be easy to measure and interpret.

• Quantify your dependent variable or use defined qualitative measures.
• Avoid overly broad or ambiguous outcomes.
• Measuring plant growth as a percentage change in height.
• Quantifying anxiety levels through standard surveys.
• Tracking click-through rates as a percentage of total views.

Tip 18: Stay Open to Unexpected Results

Not all hypotheses yield expected results.

• Be open to learning new insights, even if they contradict your prediction.
• Unexpected findings often reveal unique, significant knowledge.
• Unexpected fertilizer types boosting growth differently than anticipated.
• Screen time affecting anxiety differently across various age groups.
• Targeted ads backfiring with specific customer segments.

Tip 19: Keep Hypotheses Relevant

Ensure your hypothesis aligns with the purpose of your research.

• Avoid straying from the original question or focusing on tangential issues.
• Stick to the research scope to ensure accurate and meaningful data.
• Focus on a specific type of fertilizer for plant growth.
• Restrict studies to relevant age groups for anxiety research.
• Keep marketing hypotheses within the same target customer segment.

Tip 20: Collaborate with Peers

Collaboration strengthens hypothesis development.

• Work with colleagues or mentors for valuable feedback.
• Peer review helps identify flaws or assumptions in your hypothesis.
• Reviewing hypothesis clarity with a lab partner.
• Sharing research plans with a mentor to refine focus.
• Engaging in academic peer-review groups.

Tip 21: Re-evaluate Hypotheses Periodically

Revising hypotheses ensures relevance.

• Update based on new literature, data, or technological advances.
• A dynamic approach keeps your research current.
• Refining fertilizer studies with recent organic farming research.
• Adjusting social media hypotheses for new platforms like TikTok.
• Modifying marketing hypotheses based on changing customer preferences.

Tip 22: Develop Compelling Visuals

Illustrating hypotheses can help communicate relationships effectively.

• Use diagrams or flowcharts to show how variables interact visually.
• Infographics make it easier for others to grasp your research concept.
• A flowchart showing fertilizer effects on different plant growth stages.
• Diagrams illustrating social media use and its psychological impact.
• Infographics depicting how various marketing strategies boost engagement.

Tip 23: Refine Your Data Collection Plan

A solid data collection plan is vital for a testable hypothesis.

• Determine the best ways to measure your dependent variable.
• Ensure your data collection tools are reliable and accurate.
• Using a ruler and image analysis software to measure plant height.
• Designing standardized surveys to assess anxiety levels consistently.
• Setting up click-through tracking with analytics software.

Tip 24: Focus on Logical Progression

Ensure your hypothesis logically follows your research question.

• The relationship between variables should naturally flow from your observations.
• Avoid logical leaps that might confuse your reasoning.
• Predicting plant growth after observing effects of different fertilizers.
• Linking anxiety to social media use based on screen time studies.
• Connecting ad personalization with customer behavior data.

Tip 25: Test Against Diverse Samples

Testing across diverse samples ensures broader applicability.

• Avoid drawing conclusions from overly narrow sample groups.
• Try to include different demographics or subgroups in your testing.
• Testing fertilizer effects on multiple plant species.
• Including different age groups in anxiety research.
• Experimenting with personalized ads across varied customer segments.

Tip 26: Use Control Groups

Control groups provide a baseline for comparison.

• Compare your test group with a control group under unchanged conditions.
• This allows you to isolate the effect of your independent variable.
• Comparing plant growth with organic versus no fertilizer.
• Testing anxiety levels with and without social media breaks.
• Comparing personalized ads with general marketing content.

Tip 27: Consider Practical Constraints

Work within realistic constraints for your resources and timeline.

• Assess the feasibility of testing your hypothesis.
• Modify the hypothesis if the required testing is unmanageable.
• Reducing fertilizer types to a manageable number for testing.
• Shortening social media detox periods to realistic durations.
• Targeting only specific marketing strategies to optimize testing.

Tip 28: Recognize Bias Risks

Biases can skew hypothesis formation.

• Acknowledge your assumptions and how they may affect your research.
• Minimize biases by clearly defining and measuring variables.
• Avoiding assumptions that organic fertilizer is inherently better.
• Ensuring survey questions don’t lead to specific anxiety outcomes.
• Testing marketing strategies objectively without favoring any method.

Tip 29: Prepare for Peer Review

Peer review ensures your hypothesis holds up to scrutiny.

• Provide a clear rationale for why your hypothesis is sound.
• Address potential criticisms to strengthen your research.
• Showing your plant growth study builds on existing fertilizer research.
• Demonstrating social media anxiety links through data and literature.
• Supporting your marketing hypotheses with solid behavioral data.

Tip 30: Create a Research Proposal

A proposal outlines your hypothesis, methodology, and significance.

• It ensures your hypothesis is clear and your methods are well-thought-out.
• Proposals also help secure funding or institutional approval.
• A proposal for fertilizer studies linking plant growth and soil health.
• Research plans connecting social media habits to anxiety measures.
• Marketing proposals tying customer behavior to personalized advertising.

Tip 31: Document Your Findings

Recording findings helps validate or challenge your hypothesis.

• Document the methodology, data, and conclusions clearly.
• This allows others to verify, replicate, or expand on your work.
• Recording fertilizer effects on plant height in different soil types.
• Survey results linking social media use with anxiety levels.
• Click-through data proving personalized ads’ impact on engagement.

Check out this really good video about how to write a hypothesis:

Hypothesis Examples for Different Situations

Let’s look at some examples of how to write a hypothesis in different circumstances.

• Marketing Analysis : “If personalized ads are shown to our target demographic, then click-through rates will increase by at least 10%.”
• Process Improvement : “If automated workflows replace manual data entry, then task completion times will decrease by 20%.”
• Product Development : “If adding a chatbot feature to our app increases customer support efficiency, then user satisfaction will improve by 15%.”
• Biology Experiment : “If students grow plants with different fertilizers, then the organic fertilizer will result in slower growth compared to the chemical fertilizer.”
• Psychology Research : “If high school students take a break from social media, then their levels of anxiety will decrease.”
• Environmental Study : “If a controlled forest area is exposed to a certain pollutant, then the local plant species will show signs of damage within two weeks.”

Professional Contacts

• Medical Research : “If a novel treatment method is applied to patients with chronic illness, then their recovery rate will increase significantly compared to standard treatment.”
• Technology Research : “If machine learning algorithms analyze big data sets, then the accuracy of predictive models will surpass traditional data analysis.”
• Engineering Project : “If new composite materials replace standard components in bridge construction, then the resulting structure will be more durable.”

Super Personal

• Gardening Experiment : “If different types of compost are used in home gardens, then plants receiving homemade compost will yield the most produce.”
• Fitness Routine : “If consistent strength training is combined with a high-protein diet, then muscle mass will increase more than with diet alone.”
• Cooking Techniques : “If searing is added before baking, then the resulting roast will retain more moisture.”

Final Thoughts: How to Write a Hypothesis

Crafting hypotheses is both a science and an art. It’s about channeling curiosity into testable questions that propel meaningful discovery.

Each well-thought-out hypothesis is a stepping stone that could lead to the breakthrough you’ve been seeking.

Stay curious and let your research journey unfold.

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Educational resources and simple solutions for your research journey

What is a Research Hypothesis: How to Write it, Types, and Examples

Any research begins with a research question and a research hypothesis . A research question alone may not suffice to design the experiment(s) needed to answer it. A hypothesis is central to the scientific method. But what is a hypothesis ? A hypothesis is a testable statement that proposes a possible explanation to a phenomenon, and it may include a prediction. Next, you may ask what is a research hypothesis ? Simply put, a research hypothesis is a prediction or educated guess about the relationship between the variables that you want to investigate.  

It is important to be thorough when developing your research hypothesis. Shortcomings in the framing of a hypothesis can affect the study design and the results. A better understanding of the research hypothesis definition and characteristics of a good hypothesis will make it easier for you to develop your own hypothesis for your research. Let’s dive in to know more about the types of research hypothesis , how to write a research hypothesis , and some research hypothesis examples .  

Table of Contents

What is a hypothesis ?  

A hypothesis is based on the existing body of knowledge in a study area. Framed before the data are collected, a hypothesis states the tentative relationship between independent and dependent variables, along with a prediction of the outcome.  

What is a research hypothesis ?  

Young researchers starting out their journey are usually brimming with questions like “ What is a hypothesis ?” “ What is a research hypothesis ?” “How can I write a good research hypothesis ?”   

A research hypothesis is a statement that proposes a possible explanation for an observable phenomenon or pattern. It guides the direction of a study and predicts the outcome of the investigation. A research hypothesis is testable, i.e., it can be supported or disproven through experimentation or observation.     

Characteristics of a good hypothesis  

Here are the characteristics of a good hypothesis :  

• Clearly formulated and free of language errors and ambiguity  
• Concise and not unnecessarily verbose  
• Has clearly defined variables  
• Testable and stated in a way that allows for it to be disproven  
• Can be tested using a research design that is feasible, ethical, and practical   
• Specific and relevant to the research problem  
• Rooted in a thorough literature search  
• Can generate new knowledge or understanding.  

How to create an effective research hypothesis  

A study begins with the formulation of a research question. A researcher then performs background research. This background information forms the basis for building a good research hypothesis . The researcher then performs experiments, collects, and analyzes the data, interprets the findings, and ultimately, determines if the findings support or negate the original hypothesis.  

Let’s look at each step for creating an effective, testable, and good research hypothesis :  

• Identify a research problem or question: Start by identifying a specific research problem.   
• Review the literature: Conduct an in-depth review of the existing literature related to the research problem to grasp the current knowledge and gaps in the field.   
• Formulate a clear and testable hypothesis : Based on the research question, use existing knowledge to form a clear and testable hypothesis . The hypothesis should state a predicted relationship between two or more variables that can be measured and manipulated. Improve the original draft till it is clear and meaningful.  
• State the null hypothesis: The null hypothesis is a statement that there is no relationship between the variables you are studying.   
• Define the population and sample: Clearly define the population you are studying and the sample you will be using for your research.  
• Select appropriate methods for testing the hypothesis: Select appropriate research methods, such as experiments, surveys, or observational studies, which will allow you to test your research hypothesis .  

Remember that creating a research hypothesis is an iterative process, i.e., you might have to revise it based on the data you collect. You may need to test and reject several hypotheses before answering the research problem.  

How to write a research hypothesis  

When you start writing a research hypothesis , you use an “if–then” statement format, which states the predicted relationship between two or more variables. Clearly identify the independent variables (the variables being changed) and the dependent variables (the variables being measured), as well as the population you are studying. Review and revise your hypothesis as needed.  

An example of a research hypothesis in this format is as follows:  

“ If [athletes] follow [cold water showers daily], then their [endurance] increases.”  

Population: athletes  

Independent variable: daily cold water showers  

Dependent variable: endurance  

You may have understood the characteristics of a good hypothesis . But note that a research hypothesis is not always confirmed; a researcher should be prepared to accept or reject the hypothesis based on the study findings.  

Research hypothesis checklist  

Following from above, here is a 10-point checklist for a good research hypothesis :  

• Testable: A research hypothesis should be able to be tested via experimentation or observation.  
• Specific: A research hypothesis should clearly state the relationship between the variables being studied.  
• Based on prior research: A research hypothesis should be based on existing knowledge and previous research in the field.  
• Falsifiable: A research hypothesis should be able to be disproven through testing.  
• Clear and concise: A research hypothesis should be stated in a clear and concise manner.  
• Logical: A research hypothesis should be logical and consistent with current understanding of the subject.  
• Relevant: A research hypothesis should be relevant to the research question and objectives.  
• Feasible: A research hypothesis should be feasible to test within the scope of the study.  
• Reflects the population: A research hypothesis should consider the population or sample being studied.  
• Uncomplicated: A good research hypothesis is written in a way that is easy for the target audience to understand.  

By following this research hypothesis checklist , you will be able to create a research hypothesis that is strong, well-constructed, and more likely to yield meaningful results.  

Types of research hypothesis  

Different types of research hypothesis are used in scientific research:  

1. Null hypothesis:

A null hypothesis states that there is no change in the dependent variable due to changes to the independent variable. This means that the results are due to chance and are not significant. A null hypothesis is denoted as H0 and is stated as the opposite of what the alternative hypothesis states.   

Example: “ The newly identified virus is not zoonotic .”  

2. Alternative hypothesis:

This states that there is a significant difference or relationship between the variables being studied. It is denoted as H1 or Ha and is usually accepted or rejected in favor of the null hypothesis.  

Example: “ The newly identified virus is zoonotic .”  

3. Directional hypothesis :

This specifies the direction of the relationship or difference between variables; therefore, it tends to use terms like increase, decrease, positive, negative, more, or less.   

Example: “ The inclusion of intervention X decreases infant mortality compared to the original treatment .”   

4. Non-directional hypothesis:

While it does not predict the exact direction or nature of the relationship between the two variables, a non-directional hypothesis states the existence of a relationship or difference between variables but not the direction, nature, or magnitude of the relationship. A non-directional hypothesis may be used when there is no underlying theory or when findings contradict previous research.  

Example, “ Cats and dogs differ in the amount of affection they express .”  

5. Simple hypothesis :

A simple hypothesis only predicts the relationship between one independent and another independent variable.  

Example: “ Applying sunscreen every day slows skin aging .”  

6 . Complex hypothesis :

A complex hypothesis states the relationship or difference between two or more independent and dependent variables.   

Example: “ Applying sunscreen every day slows skin aging, reduces sun burn, and reduces the chances of skin cancer .” (Here, the three dependent variables are slowing skin aging, reducing sun burn, and reducing the chances of skin cancer.)  

7. Associative hypothesis:  

An associative hypothesis states that a change in one variable results in the change of the other variable. The associative hypothesis defines interdependency between variables.  

Example: “ There is a positive association between physical activity levels and overall health .”  

8 . Causal hypothesis:

A causal hypothesis proposes a cause-and-effect interaction between variables.  

Example: “ Long-term alcohol use causes liver damage .”  

Note that some of the types of research hypothesis mentioned above might overlap. The types of hypothesis chosen will depend on the research question and the objective of the study.  

Research hypothesis examples  

Here are some good research hypothesis examples :  

“The use of a specific type of therapy will lead to a reduction in symptoms of depression in individuals with a history of major depressive disorder.”  

“Providing educational interventions on healthy eating habits will result in weight loss in overweight individuals.”  

“Plants that are exposed to certain types of music will grow taller than those that are not exposed to music.”  

“The use of the plant growth regulator X will lead to an increase in the number of flowers produced by plants.”  

Characteristics that make a research hypothesis weak are unclear variables, unoriginality, being too general or too vague, and being untestable. A weak hypothesis leads to weak research and improper methods.   

Some bad research hypothesis examples (and the reasons why they are “bad”) are as follows:  

“This study will show that treatment X is better than any other treatment . ” (This statement is not testable, too broad, and does not consider other treatments that may be effective.)  

“This study will prove that this type of therapy is effective for all mental disorders . ” (This statement is too broad and not testable as mental disorders are complex and different disorders may respond differently to different types of therapy.)  

“Plants can communicate with each other through telepathy . ” (This statement is not testable and lacks a scientific basis.)  

Importance of testable hypothesis  

If a research hypothesis is not testable, the results will not prove or disprove anything meaningful. The conclusions will be vague at best. A testable hypothesis helps a researcher focus on the study outcome and understand the implication of the question and the different variables involved. A testable hypothesis helps a researcher make precise predictions based on prior research.  

To be considered testable, there must be a way to prove that the hypothesis is true or false; further, the results of the hypothesis must be reproducible.  

Frequently Asked Questions (FAQs) on research hypothesis  

1. What is the difference between research question and research hypothesis ?  

A research question defines the problem and helps outline the study objective(s). It is an open-ended statement that is exploratory or probing in nature. Therefore, it does not make predictions or assumptions. It helps a researcher identify what information to collect. A research hypothesis , however, is a specific, testable prediction about the relationship between variables. Accordingly, it guides the study design and data analysis approach.

2. When to reject null hypothesis ?

A null hypothesis should be rejected when the evidence from a statistical test shows that it is unlikely to be true. This happens when the test statistic (e.g., p -value) is less than the defined significance level (e.g., 0.05). Rejecting the null hypothesis does not necessarily mean that the alternative hypothesis is true; it simply means that the evidence found is not compatible with the null hypothesis.  

3. How can I be sure my hypothesis is testable?  

A testable hypothesis should be specific and measurable, and it should state a clear relationship between variables that can be tested with data. To ensure that your hypothesis is testable, consider the following:  

• Clearly define the key variables in your hypothesis. You should be able to measure and manipulate these variables in a way that allows you to test the hypothesis.  
• The hypothesis should predict a specific outcome or relationship between variables that can be measured or quantified.   
• You should be able to collect the necessary data within the constraints of your study.  
• It should be possible for other researchers to replicate your study, using the same methods and variables.   
• Your hypothesis should be testable by using appropriate statistical analysis techniques, so you can draw conclusions, and make inferences about the population from the sample data.  
• The hypothesis should be able to be disproven or rejected through the collection of data.  

4. How do I revise my research hypothesis if my data does not support it?  

If your data does not support your research hypothesis , you will need to revise it or develop a new one. You should examine your data carefully and identify any patterns or anomalies, re-examine your research question, and/or revisit your theory to look for any alternative explanations for your results. Based on your review of the data, literature, and theories, modify your research hypothesis to better align it with the results you obtained. Use your revised hypothesis to guide your research design and data collection. It is important to remain objective throughout the process.  

5. I am performing exploratory research. Do I need to formulate a research hypothesis?  

As opposed to “confirmatory” research, where a researcher has some idea about the relationship between the variables under investigation, exploratory research (or hypothesis-generating research) looks into a completely new topic about which limited information is available. Therefore, the researcher will not have any prior hypotheses. In such cases, a researcher will need to develop a post-hoc hypothesis. A post-hoc research hypothesis is generated after these results are known.  

6. How is a research hypothesis different from a research question?

A research question is an inquiry about a specific topic or phenomenon, typically expressed as a question. It seeks to explore and understand a particular aspect of the research subject. In contrast, a research hypothesis is a specific statement or prediction that suggests an expected relationship between variables. It is formulated based on existing knowledge or theories and guides the research design and data analysis.

7. Can a research hypothesis change during the research process?

Yes, research hypotheses can change during the research process. As researchers collect and analyze data, new insights and information may emerge that require modification or refinement of the initial hypotheses. This can be due to unexpected findings, limitations in the original hypotheses, or the need to explore additional dimensions of the research topic. Flexibility is crucial in research, allowing for adaptation and adjustment of hypotheses to align with the evolving understanding of the subject matter.

8. How many hypotheses should be included in a research study?

The number of research hypotheses in a research study varies depending on the nature and scope of the research. It is not necessary to have multiple hypotheses in every study. Some studies may have only one primary hypothesis, while others may have several related hypotheses. The number of hypotheses should be determined based on the research objectives, research questions, and the complexity of the research topic. It is important to ensure that the hypotheses are focused, testable, and directly related to the research aims.

9. Can research hypotheses be used in qualitative research?

Yes, research hypotheses can be used in qualitative research, although they are more commonly associated with quantitative research. In qualitative research, hypotheses may be formulated as tentative or exploratory statements that guide the investigation. Instead of testing hypotheses through statistical analysis, qualitative researchers may use the hypotheses to guide data collection and analysis, seeking to uncover patterns, themes, or relationships within the qualitative data. The emphasis in qualitative research is often on generating insights and understanding rather than confirming or rejecting specific research hypotheses through statistical testing.

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How to Write a Great Hypothesis

Hypothesis Definition, Format, Examples, and Tips

Verywell / Alex Dos Diaz

• The Scientific Method

Hypothesis Format

Falsifiability of a hypothesis.

• Operationalization

Hypothesis Types

Hypotheses examples.

• Collecting Data

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. It is a preliminary answer to your question that helps guide the research process.

Consider a study designed to examine the relationship between sleep deprivation and test performance. The hypothesis might be: "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."

At a Glance

A hypothesis is crucial to scientific research because it offers a clear direction for what the researchers are looking to find. This allows them to design experiments to test their predictions and add to our scientific knowledge about the world. 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. At this point, researchers then 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 numerous 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 adage 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.

How to Formulate a Good Hypothesis

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.

The Importance of Operational Definitions

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.

Operational definitions are specific definitions for all relevant factors in a study. This process helps make vague or ambiguous concepts detailed and measurable.

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 various ways. Clearly defining these variables and how they are measured helps ensure that other researchers can replicate your results.

Replicability

One of the basic principles of any type of scientific research is that the results must be replicable.

Replication means repeating an experiment in the same way to produce the same results. 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. For example, 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.

To measure this variable, the researcher must devise a measurement that assesses aggressive behavior without harming others. The researcher might utilize a simulated task to measure aggressiveness in this situation.

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 there is a relationship between one independent variable and one dependent variable.
• Complex hypothesis : This type suggests a relationship between three or more variables, such as two independent and dependent variables.
• 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 population sample 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."
• "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."
• "Children who receive a new reading intervention will have higher reading scores than students who do not receive the intervention."

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:

• "There is no difference in anxiety levels between people who take St. John's wort supplements and those who do not."
• "There is no difference in scores on a memory recall task between children and adults."
• "There is no difference in aggression levels between children who play first-person shooter games and those who do not."

Examples of an alternative hypothesis:

• "People who take St. John's wort supplements will have less anxiety than those who do not."
• "Adults will perform better on a memory task than children."
• "Children who play first-person shooter games will show higher levels of aggression than children who do not." 

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  conducting an experiment is difficult or impossible. 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 examine how the variables are related. This 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.

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.

Thompson WH, Skau S. On the scope of scientific hypotheses .  R Soc Open Sci . 2023;10(8):230607. doi:10.1098/rsos.230607

Taran S, Adhikari NKJ, Fan E. Falsifiability in medicine: what clinicians can learn from Karl Popper [published correction appears in Intensive Care Med. 2021 Jun 17;:].  Intensive Care Med . 2021;47(9):1054-1056. doi:10.1007/s00134-021-06432-z

Eyler AA. Research Methods for Public Health . 1st ed. Springer Publishing Company; 2020. doi:10.1891/9780826182067.0004

Nosek BA, Errington TM. What is replication ?  PLoS Biol . 2020;18(3):e3000691. doi:10.1371/journal.pbio.3000691

Aggarwal R, Ranganathan P. Study designs: Part 2 - Descriptive studies .  Perspect Clin Res . 2019;10(1):34-36. doi:10.4103/picr.PICR_154_18

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."

eslwriting.org

A panoply of teaching resources.

Writing Hypothesis Sentences

Some English students have a hard time expressing complex ideas in short sentences. They don’t know how to summarize or synthesize information. This short lesson helps students overcome that barrier by teaching them how to construct a hypothesis with an easy to learn sentence pattern. 

Lesson Objectives

By the end of this lesson, students should be able to:

• define hypothesis
• use it to communicate and synthesize complex ideas

Student Level: intermediate +

Lesson time: 50-75 minutes

Extra resource: pdf file with images and suggested answers for class review .

Part 1. Overview: Hypothesis Sentence Pattern (10 minutes)

A hypothesis is a sentence which shows us how two different things are connected. There are many ways to write a hypothesis. This lessons focuses on one sentence pattern because it is easy to understand and use.

Here are some examples:

• The more water a plant gets, the faster the plant will grow.
• The more I study , the more I learn.
• The richer the country, the more waste is produced.
• The hotter the temperature , the more ice cream people buy.

When writing a hypothesis sentence, it is important to remember this:

• The things you are looking at must be measurable. These are called variables.
• That means, we have to be able to count or measure quantify the variables we are trying to connect.

Now look at the key words in the 4 hypothesis sentences above. How can we measure these different things?

Check this file for a few possible answers .

Part 2: Practice #1 (10 minutes)

In this short task, students apply their new found knowledge of the hypothesis sentence pattern. The task uses a famous video clip with Steve Jobs .

Step 1: Introduce video clip. It is a small part of a speech made by Steve Jobs at a university convocation.

Step 2: Students listen to the video and summarize the main idea in the form of a hypothesis sentence pattern.

Step 3: Play video 2-3 times.

Step 4: Students to work in pairs and create one hypothesis sentence that summarizes the speaker’s main idea.

Step 5: Review answers in class. 

Part 3: Practice #2 (10 minutes)

Another practice round where students summarize data by creating hypothesis sentences. The suggested teaching approach is a pair work fluency drill.

Step 1: Put students in pairs or small groups.

Step 2: Introduce task. Students look at an image for one minute. They write one sentence hypothesis sentence that summarizes the data.

Step 3: Show the first image as a group practice effort.

Step 4: Give students 1 to 2 minutes to study the image and write a hypothesis sentence with their partner.

Step 5: After time has passed, review answers in class. 

Step 6: Begin the drill. Show each image for 1 – 2 minutes, or enough time for students to think about, create and write down one hypothesis statement.

Step 7: After all images have been examined, review sentences on whiteboard with whole class.

Here are some images and data sets for the drill:

Check this file to few the graphs and show some  possible answers .

Part 4: World History Video Summary (20-40 minutes)

This video shows the history of Earth . 200 years of change in 4 minutes. It is a unique presentation that will help build your students’ vocabulary and listening skills. The video is also a good example of telling a great story with hypothesis sentences.

Step 1. Watch the video one time.

Step 2. Make notes and answer these questions with a partner.

• What is the variable for each axis on the graph?
• How is each variable counted or measured?
• Write one hypothesis sentence using the data from the video.

Step 3. Discuss answers with whole class.

Step 4. Write a paragraph or more to explain the cause and effect relationship in the hypothesis.

Optional Step: Vocabulary Preview

Depending on the needs of your class, it might be a good idea to preview some vocabulary before students watch the video. Here are some words and phrases critical to video comprehension.

• life expectancy
• income per person
• Middle East
• industrial revolution
• Great Depression
• to catch up
• inequalities

Enjoy the lesson. Cheers!

Teach writing?

If you teach writing in an EFL classroom, why not buy a useful resource,  Teach Essential Writing Skills . Transform the quality of EFL student writing by focusing on four essential skills. Click here for details about the ebook that should be part of every writing teacher’s resource library.

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3 thoughts on “writing hypothesis sentences”.

Great site!

Thank you for the video. I can understand it, but I can’t define or explain it in ratio form. Please define and answer your question for me, so I can better understand. Thank you again.

Really good explanation. I’ll try to use it during lessons. I like a lot creative lessons ant this is one of them.

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• Knowledge Base

Hypothesis Testing | A Step-by-Step Guide with Easy Examples

Published on November 8, 2019 by Rebecca Bevans . Revised on June 22, 2023.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics . It is most often used by scientists to test specific predictions, called hypotheses, that arise from theories.

There are 5 main steps in hypothesis testing:

• State your research hypothesis as a null hypothesis and alternate hypothesis (H o ) and (H a  or H 1 ).
• Collect data in a way designed to test the hypothesis.
• Perform an appropriate statistical test .
• Decide whether to reject or fail to reject your null hypothesis.
• Present the findings in your results and discussion section.

Though the specific details might vary, the procedure you will use when testing a hypothesis will always follow some version of these steps.

Table of contents

Step 1: state your null and alternate hypothesis, step 2: collect data, step 3: perform a statistical test, step 4: decide whether to reject or fail to reject your null hypothesis, step 5: present your findings, other interesting articles, frequently asked questions about hypothesis testing.

After developing your initial research hypothesis (the prediction that you want to investigate), it is important to restate it as a null (H o ) and alternate (H a ) hypothesis so that you can test it mathematically.

The alternate hypothesis is usually your initial hypothesis that predicts a relationship between variables. The null hypothesis is a prediction of no relationship between the variables you are interested in.

• H 0 : Men are, on average, not taller than women. H a : Men are, on average, taller than women.

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For a statistical test to be valid , it is important to perform sampling and collect data in a way that is designed to test your hypothesis. If your data are not representative, then you cannot make statistical inferences about the population you are interested in.

There are a variety of statistical tests available, but they are all based on the comparison of within-group variance (how spread out the data is within a category) versus between-group variance (how different the categories are from one another).

If the between-group variance is large enough that there is little or no overlap between groups, then your statistical test will reflect that by showing a low p -value . This means it is unlikely that the differences between these groups came about by chance.

Alternatively, if there is high within-group variance and low between-group variance, then your statistical test will reflect that with a high p -value. This means it is likely that any difference you measure between groups is due to chance.

Your choice of statistical test will be based on the type of variables and the level of measurement of your collected data .

• an estimate of the difference in average height between the two groups.
• a p -value showing how likely you are to see this difference if the null hypothesis of no difference is true.

Based on the outcome of your statistical test, you will have to decide whether to reject or fail to reject your null hypothesis.

In most cases you will use the p -value generated by your statistical test to guide your decision. And in most cases, your predetermined level of significance for rejecting the null hypothesis will be 0.05 – that is, when there is a less than 5% chance that you would see these results if the null hypothesis were true.

In some cases, researchers choose a more conservative level of significance, such as 0.01 (1%). This minimizes the risk of incorrectly rejecting the null hypothesis ( Type I error ).

The results of hypothesis testing will be presented in the results and discussion sections of your research paper , dissertation or thesis .

In the results section you should give a brief summary of the data and a summary of the results of your statistical test (for example, the estimated difference between group means and associated p -value). In the discussion , you can discuss whether your initial hypothesis was supported by your results or not.

In the formal language of hypothesis testing, we talk about rejecting or failing to reject the null hypothesis. You will probably be asked to do this in your statistics assignments.

However, when presenting research results in academic papers we rarely talk this way. Instead, we go back to our alternate hypothesis (in this case, the hypothesis that men are on average taller than women) and state whether the result of our test did or did not support the alternate hypothesis.

If your null hypothesis was rejected, this result is interpreted as “supported the alternate hypothesis.”

These are superficial differences; you can see that they mean the same thing.

You might notice that we don’t say that we reject or fail to reject the alternate hypothesis . This is because hypothesis testing is not designed to prove or disprove anything. It is only designed to test whether a pattern we measure could have arisen spuriously, or by chance.

If we reject the null hypothesis based on our research (i.e., we find that it is unlikely that the pattern arose by chance), then we can say our test lends support to our hypothesis . But if the pattern does not pass our decision rule, meaning that it could have arisen by chance, then we say the test is inconsistent with our hypothesis .

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

• Normal distribution
• Descriptive statistics
• Measures of central tendency
• Correlation coefficient

Methodology

• Cluster sampling
• Stratified sampling
• Types of interviews
• Cohort study
• Thematic analysis

Research bias

• Implicit bias
• Cognitive bias
• Survivorship bias
• Availability heuristic
• Nonresponse bias
• Regression to the mean

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 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).

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.

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HYPOTHESIS in a Sentence Examples: 21 Ways to Use Hypothesis

Have you ever wondered what a “hypothesis” is and how it fits into the scientific method? A hypothesis is a proposed explanation or educated guess that can be tested through research and experimentation to determine its validity.

Table of Contents

7 Examples Of Hypothesis Used In a Sentence For Kids

14 sentences with hypothesis examples, how to use hypothesis in sentences.

Hypothesis is an educated guess or prediction that can be tested through observation or experimentation. When incorporating this term into a sentence, it is important to clearly identify it so readers can understand its significance.

Here are some tips on how to use hypothesis effectively in a sentence:

Clearly state your hypothesis in a simple and concise manner. For example, “The scientist’s hypothesis is that plants will grow faster with added sunlight.”

Make sure to refer back to your hypothesis when discussing the results of your experiment. For example, “The data supported our initial hypothesis that exercise leads to improved cardiovascular health.”

By following these guidelines, you can effectively incorporate hypothesis into your writing to communicate your predictions or expectations clearly and accurately.

In conclusion, sentences with the keyword “hypothesis” often express a proposed explanation or prediction that can be tested through research or observation. These sentences play a crucial role in scientific inquiry by guiding investigations and exploring relationships between variables. For example, “The researchers formulated a hypothesis to predict the effect of sunlight on plant growth” demonstrates how hypotheses are used to frame a study’s objectives and outcomes.

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Complex Sentences: 50 Examples

What is a complex sentence?

A  complex sentence  contains one independent clause and one or more dependent clauses.

An  independent clause  contains a subject and verb , and can stand alone as a complete sentence:

• Independent clause: I love going outside.

A  dependent clause also contains a subject and verb , but it cannot stand alone as a complete sentence. Instead, it ADDS information to the sentence:

• Dependent clause: when the weather is warm.

One independent clause + one dependent clause = a complex sentence:

• I love going outside when the weather is warm.

Dependent clauses often start with  subordinating conjunctions,  for example:

• provided that

Subordinating conjunctions often show a cause-and-effect relationship or a relationship of time/place:

• Cause and effect relationship: The baseball game was canceled because it was raining.
• Time relationship: When I get home from work, I always take off my shoes.
• Place relationship: Make sure to put on sunscreen wherever your skin is exposed.

Learn more about subordinating conjunctions.

Download this lesson!

Difference between a compound sentence and a complex sentence

A  compound sentence   contains two  independent  clauses joined by a coordinating conjunction (and, but, or, so, yet):

• I’m happy, but my kids are always complaining. ( “I’m happy” can be a complete sentence. “My kids are always complaining” can also be a complete sentence. They are joined by the coordinating conjunction “but”)
• The blue jacket cost over $100 , and he wears it every day . (“The blue jacket cost over $100” is a complete sentence. “He wears it every day” is a complete sentence. They are joined by the coordinating conjunction “and”)

A  complex sentence  contains one independent clause and one or more  dependent clauses,  joined by a subordinating conjunction or a relative pronoun (that, who, which):

• I’m happy because we won the game. (“I’m happy” can be a complete sentence. “Because we won the game” cannot be a sentence by itself.)
• The blue jacket, which I gave him for Christmas, cost over $100. (“The blue jacket cost over $100” is a complete sentence. “which I gave him for Christmas” is NOT a complete sentence. They are joined by the relative pronoun “which”)

Difference between a dependent clause and a prepositional phrase

Words like before, after, since, and until can begin either a dependent clause or a prepositional phrase.

The main difference is that a dependent clause has a subject and verb, but a prepositional phrase does not:

• I’ll wait here until you get back. (dependent clause: you = subject, get = verb)
• I’ll wait here until 5:30. (prepositional phrase: no subject/verb after “until”)
• He’s never been the same since he broke up with his girlfriend. (dependent clause: he = subject, broke up = verb)
• He’s never been the same since the car accident. (prepositional phrase: no subject/verb after “since”)

Complex Sentences: Simple Present Tense

The independent clause in bold , and the dependent clause is underlined:

• Although he works long hours, he always finds time to spend with his family.
• She always wears jewelry that matches her outfit.
• While my brother enjoys spicy food, I prefer milder flavors.
• Several crops grow here, even though it rarely rains in this region.
• Though he is talented, he often underestimates his own abilities.
• Although the company faces tough competition, it continues to thrive in the market.
• I think you’d like this book, since you love historical fiction.
• He always studies a lot before he takes a test.
• I sometimes walk to work, as long as the weather is good.
• My mother stays up late, whereas my father goes to bed early.

Complex Sentences: Simple Past Tense

• After she finished her studies, she traveled around Europe for six months.
• Although they were tired, they stayed up late to finish their projec t.
• He immediately called for help when he saw the accident.
• My kids often misbehaved whenever they had a babysitter.
• Since he sold his car, he had to take the bus to work.
• She didn’t ride the roller coasters, even though she was old enough to do so.
• When they arrived at the restaurant, they realized it had already closed.
• I stayed awake until my husband got home from work.
• Before he left his job, he wrote a number of training manuals.
• She performed very well on stage,  though she was quite nervous.

Complex Sentences: Future Tenses in the Independent Clause

• After I finish my degree, I will pursue a career in environmental conservation.
• She will visit her grandparents next weekend, as she hasn’t seen them in months.
• Once the project is complete, the company will launch its new product on the market.
• By the time I graduate, I will have traveled to at least five different countries.
• We’re going to clean the bathrooms after we’re done cleaning the kitchen.
• They will be driving to Florida since flights are too expensive.
• Electric cars will become more popular in a few years, even though they’re not very common now.
• I’m going to start preparing dinner before I leave for work.
• Once the renovations are finished, the house will be even more beautiful.
• I won’t lend you any more money  until you pay me back.

Complex Sentences: Continuous Verb Tenses in the Independent Clause

• While I was studying for my exam, my friends were watching a movie.
• They will be traveling to Europe while we are attending the conference.
• As the sun was setting , the children were playing in the park.
• I was cleaning the house all evening after I saw how dirty it was.
• I’ll be waiting for you at the  café   until you finish your meeting.

Complex Sentence Examples: Mixed Verb Tenses

• When I finish my work, I will join you for dinner.
• I had cleaned the whole house before we left for vacation.
• He couldn’t go to the party because he was feeling sick.
• I’m not buying anything else this month   since I’ve already spent too much.
• As soon as they receive the necessary materials, they will start the project.
• Once she finishes her degree, she plans to travel the world.
• I was exhausted because I had been working all day.
• Now that the rain has stopped, we can go outside.
• He will buy a new car once he saves enough money.
• Since she doesn’t have any prior experience, she decided to take a training course.

Complex Sentence Examples: Conditionals

Some of the most common complex sentences are conditional sentences like the examples below. Again, the independent clause (result) is in  bold,  and the dependent clause (condition) is  underlined.

• If it rains tomorrow, we will stay indoors and watch movies.
• She won’t pass the exam unless she studies a lot.
• If I won the lottery, I would travel around the world.
• He would have gone to the party if he hadn’t been so tired.
• If I had known about the event, I would have attended.
• She will be late if she doesn’t catch the early bus.
• If the children finish their chores , they can go to the park.
• We won’t eat a big dinner if we’re not very hungry.
• If you eat too much junk food, you will gain weight.
• She could earn more money if she had a better job.

Learn more about first conditional and second conditional.

More examples of sentence structures:

• Simple sentences: 50 examples
• Compound sentences: 50 examples
• Simple, compound, complex, and compound-complex sentences

Master the details of English grammar:

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Simple Hypothesis

Ai generator.

Venturing into the realm of scientific inquiry, the hypothesis stands as a beacon, guiding researchers towards answers. A simple hypothesis, crisp and to the point, paves the way for clear testing and straightforward results. But how does one draft such a potent statement? And what makes it so effective? Join us as we demystify the art of creating simple hypothesis statements and share invaluable tips to refine your approach.”

What is an example of a Simple hypothesis statement?

A simple hypothesis statement typically specifies a relationship or difference between two variables. Here’s an example:

Caffeine Consumption and Alertness: Consuming caffeine increases a person’s alertness.

In this example, the two variables are “caffeine consumption” and “alertness.” The hypothesis simply posits that there’s a direct relationship between these two variables, indicating that as one (caffeine consumption) increases, the other (alertness) does as well.

100 Simple Hypothesis Statement Examples

Size: 166 KB

Simple hypothesis statements act as the backbone of research, succinctly proposing a direct relationship or difference between two variables. These straightforward declarations pave the way for clear testing and results, offering a digestible insight into expected outcomes.

• Sunlight and Plant Growth : Exposure to sunlight increases plant growth.
• Reading and Vocabulary Expansion : Regular reading leads to an expanded vocabulary.
• Exercise and Heart Health : Engaging in exercise improves heart health.
• Sugar Intake and Energy Levels : Consuming sugar temporarily boosts energy levels.
• Hydration and Skin Health : Drinking water improves skin hydration.
• Meditation and Stress Reduction : Practicing meditation reduces stress levels.
• Music and Productivity : Listening to music enhances work productivity.
• Sleep Duration and Cognitive Functions : Getting adequate sleep improves cognitive functions.
• Fertilizer and Crop Yield : Using fertilizers increases crop yields.
• Probiotics and Gut Health : Consuming probiotics enhances gut health.
• Screen Time and Eye Strain : Prolonged screen time leads to increased eye strain.
• Social Media Usage and Loneliness : Frequent social media use is linked to feelings of loneliness.
• Carbon Emissions and Global Warming : Higher carbon emissions contribute to global warming.
• Vitamin C and Immunity : Consuming vitamin C boosts immune functions.
• Artificial Lights and Sleep Quality : Exposure to artificial lights at night reduces sleep quality.
• Yoga and Flexibility : Regular yoga practice increases flexibility.
• Chocolate Consumption and Mood : Eating chocolate elevates mood.
• Brushing and Dental Health : Regular brushing reduces dental cavities.
• Temperature and Metabolism Rate : Cold environments accelerate metabolism.
• Pet Ownership and Happiness : Having a pet contributes to increased happiness levels.
• Puzzles and Brain Activity : Solving puzzles activates brain functions.
• Green Tea and Weight Loss : Drinking green tea aids in weight loss.
• Salt Intake and Blood Pressure : Consuming high amounts of salt raises blood pressure.
• Indoor Plants and Air Quality : Having indoor plants improves air quality.
• Antibiotics and Bacterial Infections : Taking antibiotics reduces bacterial infections.
• Laughter and Endorphin Release : Engaging in laughter releases endorphins.
• Gaming and Hand-Eye Coordination : Playing video games improves hand-eye coordination.
• Washing Hands and Germ Spread : Regular hand washing reduces the spread of germs.
• Spicy Foods and Metabolism : Consuming spicy foods boosts metabolism.
• Journaling and Emotional Health : Maintaining a journal aids emotional well-being.
• Urban Areas and Noise Pollution : Urban regions are associated with higher noise pollution.
• Physical Activity and Bone Density : Regular physical activity strengthens bone density.
• Aloe Vera and Skin Soothing : Applying aloe vera soothes skin irritations.
• Alcohol Consumption and Reaction Time : Drinking alcohol slows down reaction time.
• Bird Watching and Patience : Engaging in bird watching cultivates patience.
• Cycling and Leg Strength : Regular cycling enhances leg muscle strength.
• Public Speaking and Confidence : Practicing public speaking boosts confidence.
• Dancing and Cardiovascular Health : Dancing regularly improves cardiovascular health.
• Acupuncture and Pain Relief : Undergoing acupuncture reduces pain.
• Caloric Restriction and Lifespan : Reducing caloric intake is linked to extended lifespan.
• Olive Oil and Heart Health : Consuming olive oil promotes heart health.
• Mindfulness and Attention Span : Practicing mindfulness increases attention span.
• Bilingualism and Cognitive Flexibility : Being bilingual enhances cognitive flexibility.
• Heavy Metals and Water Toxicity : Presence of heavy metals increases water toxicity.
• Mountain Climbing and Stamina : Engaging in mountain climbing builds stamina.
• Urbanization and Wildlife Displacement : Increased urbanization leads to wildlife displacement.
• Mentoring and Career Progression : Having a mentor accelerates career progression.
• Organic Farming and Soil Health : Practicing organic farming enhances soil health.
• Red Wine and Antioxidant Intake : Consuming red wine increases antioxidant intake.
• Studying Abroad and Cultural Awareness : Studying abroad enhances cultural awareness.
• E-books and Reading Duration : Using e-books extends reading duration.
• Swimming and Lung Capacity : Regular swimming increases lung capacity.
• Deforestation and Carbon Dioxide Levels : Deforestation raises carbon dioxide levels.
• Fast Food and Obesity : Frequent fast food consumption is linked to obesity.
• Classical Music and Infant Sleep : Playing classical music improves infant sleep duration.
• Microplastics and Marine Pollution : The presence of microplastics heightens marine pollution.
• Afforestation and Rainfall : Increasing forest cover can lead to higher rainfall.
• Gratitude Journaling and Positivity : Maintaining a gratitude journal boosts feelings of positivity.
• Singing and Lung Function : Regular singing enhances lung function.
• Noise Pollution and Stress : Exposure to noise pollution increases stress levels.
• Rural Living and Mental Peace : Living in rural areas promotes mental peace.
• Soft Drinks and Bone Density : Consuming soft drinks decreases bone density.
• Travel and Open-mindedness : Traveling frequently fosters open-mindedness.
• Digital Learning and Student Engagement : Digital learning tools increase student engagement.
• Plastic Usage and Land Pollution : Increased plastic usage contributes to land pollution.
• Stretching and Muscle Flexibility : Daily stretching improves muscle flexibility.
• Wine Consumption and Gut Health : Moderate wine consumption benefits gut health.
• Homework and Academic Achievement : Regular homework boosts academic achievement.
• Raw Foods and Digestive Health : Consuming raw foods aids digestive health.
• High Heels and Posture : Wearing high heels affects posture negatively.
• Therapy and Mental Well-being : Engaging in therapy promotes mental well-being.
• Fast Charging and Battery Lifespan : Using fast charging can reduce battery lifespan.
• Pottery and Hand Dexterity : Practicing pottery improves hand dexterity.
• Group Study and Retention : Studying in groups enhances information retention.
• Red Meat and Cholesterol Levels : Consuming red meat increases cholesterol levels.
• Kombucha and Gut Flora : Drinking kombucha benefits gut flora.
• Night Driving and Accident Risk : Driving at night increases the risk of accidents.
• Karaoke and Social Bonding : Engaging in karaoke fosters social bonding.
• Balanced Diet and Energy Levels : Following a balanced diet boosts energy levels.
• Multitasking and Task Efficiency : Multitasking reduces task efficiency.
• Gardening and Stress Relief : Regular gardening acts as a stress reliever.
• Digital Detox and Sleep Quality : Undertaking a digital detox improves sleep quality.
• Massage and Muscle Relaxation : Getting massages aids muscle relaxation.
• Animal Therapy and Emotional Healing : Engaging with animals accelerates emotional healing.
• Crafting and Creativity : Regular crafting activities enhance creativity.
• Organ Donation and Life-saving : Organ donation can be life-saving.
• Bamboo Products and Sustainability : Using bamboo products promotes sustainability.
• Weight Training and Muscle Mass : Engaging in weight training increases muscle mass.
• Fermented Foods and Digestion : Consuming fermented foods aids digestion.
• Outdoor Activities and Vitamin D Levels : Engaging in outdoor activities boosts Vitamin D levels.
• Smoking and Lung Health : Regular smoking deteriorates lung health.
• Feedback and Performance Improvement : Receiving feedback improves performance.
• Adventure Sports and Risk-taking Ability : Engaging in adventure sports enhances risk-taking ability.
• Coding and Logical Thinking : Learning to code promotes logical thinking.
• Chocolate and Antioxidant Levels : Eating dark chocolate boosts antioxidant levels.
• Vegetarian Diet and Heart Health : Following a vegetarian diet improves heart health.
• Deep Breathing and Relaxation : Practicing deep breathing induces relaxation.
• Natural Light and Productivity : Exposure to natural light enhances productivity.
• Green Spaces and Mental Health : Access to green spaces boosts mental well-being.
• Recycling and Resource Conservation : Regular recycling promotes resource conservation.

Simple Hypothesis Statement Examples for Kids

Kids often view the world with endless curiosity. Simplified hypotheses allow them to test their surroundings and grasp scientific methods. These Hypothesis for kids statements, tailored for young inquisitors, provide clear cause-and-effect scenarios to foster their learning.

• Ice Melting : Placing ice in the sun will make it melt faster than in the shade.
• Plant Growth : Plants kept near the window grow taller than plants in dark corners.
• Pet’s Activity : Dogs are more active during the day than at night.
• Toy Durability : Soft toys tear more easily than hard plastic toys.
• Sleep Patterns : Going to bed late makes you feel more tired the next morning.
• Food Preference : Cats prefer fish-flavored food over chicken-flavored food.
• Shadow Formation : Standing against the light creates longer shadows during the evening.
• Bubble Size : Using more soap in water creates bigger bubbles.
• Learning Speed : Kids remember rhymes faster with music than without.
• Color Attraction : Brightly colored toys attract more attention than dull-colored ones.

Simple Hypothesis Statement Examples for Research Paper

In academic settings, crafting a straightforward hypothesis helps anchor a research paper, allowing readers to quickly understand the focal point. Here are concise research hypothesis statements ideal for academic exploration.

• Diet and Cholesterol : A Mediterranean diet lowers cholesterol levels more effectively than a Western diet.
• Urban Development : Rapid urbanization leads to increased air pollution.
• Language Acquisition : Immersion learning accelerates second language acquisition compared to classroom learning.
• Climate Change : Increasing global temperatures directly correlate with rising sea levels.
• Digital Learning : Online education reduces classroom engagement levels.
• Consumer Behavior : Discount offers increase sales during festive seasons.
• Migration Patterns : Economic downturns in a region trigger increased migration.
• Environmental Conservation : Protected wildlife zones reduce species extinction rates.
• Cultural Influence : Exposure to global media diminishes local cultural practices.
• Public Health : Regular public health campaigns reduce the spread of infectious diseases.

Simple Hypothesis Statement Examples for Nursing

In nursing, hypotheses aim to shed light on patient care, health outcomes, and the intricacies of the medical field. These focused statements offer directions for nursing research and practice.

• Post-Operative Recovery : Patients with post-operative physiotherapy recover faster than those without.
• Pain Management : Music therapy reduces the need for pain medication in chronic pain patients.
• Infant Care : Skin-to-skin contact immediately after birth strengthens mother-infant bonding.
• Elderly Health : Regular social interactions decrease the onset of dementia in the elderly.
• Disease Awareness : Regular health check-ups reduce late-stage disease diagnoses.
• Mental Health : Group therapy sessions enhance coping mechanisms for depression patients.
• Patient Satisfaction : Nurse-patient ratios are directly proportional to patient satisfaction rates.
• Medication Adherence : Simplified medication regimens increase adherence in elderly patients.
• Diet and Recovery : High protein diets speed up wound healing in hospitalized patients.
• Sleep and Health : Night-shift workers report higher levels of fatigue than day-shift workers.

Simple Hypothesis Statement Examples in Psychology

Psychology delves deep into the human psyche. Simple pyschology hypothesis in this domain assist in understanding behavioral patterns, cognitive functions, and emotional dynamics. Here are statements reflective of common psychological queries.

• Child Behavior : Children exposed to violent media exhibit more aggressive behaviors.
• Memory and Age : Memory recall decreases with advancing age.
• Group Dynamics : Individuals in larger groups are less likely to exhibit helping behaviors.
• Stress and Performance : Moderate levels of stress enhance performance on cognitive tasks.
• Mood and Perception : Positive moods increase the likelihood of optimistic future expectations.
• Learning Styles : Visual learners retain graphic information better than auditory information.
• Emotions and Decision Making : Intense emotions impair rational decision-making processes.
• Peer Pressure : Adolescents are more likely to engage in risk-taking behaviors under peer influence.
• Personality and Career Choices : Introverts are more drawn to independent job roles than extroverts.
• Dream Patterns : Exposure to traumatic events increases the frequency of nightmares.

Simple Hypothesis Statement Examples for Research

Effective research begins with a precise hypothesis. These straightforward declarations guide the investigative journey, providing clarity in discerning outcomes and assessing implications.

• Technology and Employment : Automation in industries leads to a reduction in manual jobs.
• Marketing Techniques : Influencer marketing garners more engagement than traditional advertising.
• Environmental Initiatives : Implementing green technologies reduces corporate carbon footprints.
• Dietary Habits : Vegan diets result in lower carbon footprints than omnivorous diets.
• Economic Policies : Tax breaks for the middle class stimulate economic growth.
• Educational Systems : Student-led learning methods increase long-term knowledge retention.
• Public Policies : Urban green spaces correlate with reduced crime rates.
• Cultural Shifts : Increased global travel promotes intercultural understanding and tolerance.
• Health Trends : Veganism leads to reduced risks of heart-related diseases.
• Digital Consumption : Increased screen time is linked to declining mental well-being.

Simple vs Complex Hypothesis example

When it comes to scientific research, hypotheses play a pivotal role in guiding investigations. At the core, a hypothesis is a statement about a potential relationship between variables, or an explanation of an occurrence, which is testable. Based on their structural and conceptual nature, hypotheses can be categorized into simple and complex.

A simple hypothesis is a statement that explains the relationship between two variables – one independent variable and one dependent variable. Because it explains the expected relationship in the simplest form, it’s straightforward to test.

Example: Drinking caffeine improves short-term memory.

In this example:

• Independent Variable : Caffeine consumption
• Dependent Variable : Short-term memory

Complex Hypothesis

A complex good hypothesis , in contrast, deals with the relationship between two or more independent variables and two or more dependent variables. This means it’s multidimensional and requires more intricate testing procedures.

Example: Consuming caffeine and sugar together improves short-term memory and reaction time better than consuming either alone.

• Independent Variables : Caffeine consumption and sugar consumption
• Dependent Variables : Short-term memory and reaction time

How do you write a Simple hypothesis statement? – A Step by Step Guide

Step 1: identify your research question.

Every hypothesis stems from a research question. For instance, “Does sunlight affect plant growth?” From this, you can create your hypothesis.

Step 2: Determine the Variables

Every hypothesis has two essential variables:

• Independent Variable : The cause or reason. (Sunlight in our example)
• Dependent Variable : The effect or outcome. (Plant growth in our example)

Step 3: Formulate the Relationship

Specify the expected relationship between the independent and dependent variable. It might be a positive correlation, negative correlation, or no correlation.

Step 4: Keep It Testable

Ensure your hypothesis can be tested empirically. It should be specific enough that experiments or observations can prove or disprove it.

Step 5: Write the Statement

Now, construct your statement. For our example, a potential hypothesis might be: Exposing plants to more sunlight will result in faster growth.

Tips for Writing Simple Hypothesis

• Stay Focused : Stick to one specific relationship between an independent and dependent variable. Avoid including multiple causes or effects to keep it simple.
• Be Clear & Concise : Use clear, straightforward language. Avoid jargon unless it’s necessary for specificity.
• Ensure It’s Testable : A hypothesis is only useful if you can test it. Avoid abstract or overly broad statements.
• Base on Existing Research : While your hypothesis will guide new research, it should be grounded in existing theories or observations.
• Avoid Bias : Ensure your hypothesis doesn’t show any personal beliefs or inclinations. It should be neutral.
• Revisit & Refine : After writing, revisit your hypothesis. Does it still align with your research question? Is there a clearer way to phrase it?
• Stay Open to Changes : Based on the results of your tests or experiments, be prepared to change or adjust your hypothesis.

Remember, a hypothesis is an educated guess. It’s not a definitive explanation, but rather a proposed one, and its primary purpose is to guide your research. Whether your hypothesis gets supported or refuted, the insights you gain are invaluable.

Text prompt

• Instructive
• Professional

10 Examples of Public speaking

20 Examples of Gas lighting

How to Use hypothesis in a Sentence

• The results of the experiment did not support his hypothesis .
• Their hypothesis is that watching excessive amounts of television reduces a person's ability to concentrate.
• Other chemists rejected his hypothesis .

Some of these examples are programmatically compiled from various online sources to illustrate current usage of the word 'hypothesis.' Any opinions expressed in the examples do not represent those of Merriam-Webster or its editors. Send us feedback about these examples.

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