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- How to Write a Strong Hypothesis | Steps & Examples

How to Write a Strong Hypothesis | Steps & Examples
Published on May 6, 2022 by Shona McCombes . Revised on December 2, 2022.
A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection .
Example: Hypothesis
Daily apple consumption leads to fewer doctor’s visits.
Table of contents
What is a hypothesis, developing a hypothesis (with example), hypothesis examples, frequently asked questions about writing hypotheses.
A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.
A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).
Variables in hypotheses
Hypotheses propose a relationship between two or more types of variables .
- An independent variable is something the researcher changes or controls.
- A dependent variable is something the researcher observes and measures.
If there are any control variables , extraneous variables , or confounding variables , be sure to jot those down as you go to minimize the chances that research bias will affect your results.
In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .
Step 1. Ask a question
Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.
Step 2. Do some preliminary research
Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.
At this stage, you might construct a conceptual framework to ensure that you’re embarking on a relevant topic . This can also help you identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalize more complex constructs.
Step 3. Formulate your hypothesis
Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.
4. Refine your hypothesis
You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:
- The relevant variables
- The specific group being studied
- The predicted outcome of the experiment or analysis
5. Phrase your hypothesis in three ways
To identify the variables, you can write a simple prediction in if…then form. The first part of the sentence states the independent variable and the second part states the dependent variable.
In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.
If you are comparing two groups, the hypothesis can state what difference you expect to find between them.
6. Write a null hypothesis
If your research involves statistical hypothesis testing , you will also have to write a null hypothesis . The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .
- H 0 : The number of lectures attended by first-year students has no effect on their final exam scores.
- H 1 : The number of lectures attended by first-year students has a positive effect on their final exam scores.
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A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).
Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.
Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.
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How to Write a Hypothesis in 6 Steps
A hypothesis is a statement that explains the predictions and reasoning of your research—an “educated guess” about how your scientific experiments will end. As a fundamental part of the scientific method, a good hypothesis is carefully written, but even the simplest ones can be difficult to put into words.
Want to know how to write a hypothesis for your academic paper ? Below we explain the different types of hypotheses, what a good hypothesis requires, the steps to write your own, and plenty of examples.
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What is a hypothesis?
One of our 10 essential words for university success , a hypothesis is one of the earliest stages of the scientific method. It’s essentially an educated guess—based on observations—of what the results of your experiment or research will be.
If you’ve noticed that watering your plants every day makes them grow faster, your hypothesis might be “plants grow better with regular watering.” From there, you can begin experiments to test your hypothesis; in this example, you might set aside two plants, water one but not the other, and then record the results to see the differences.
The language of hypotheses always discusses variables , or the elements that you’re testing. Variables can be objects, events, concepts, etc.—whatever is observable.
There are two types of variables: independent and dependent. Independent variables are the ones that you change for your experiment, whereas dependent variables are the ones that you can only observe. In the above example, our independent variable is how often we water the plants and the dependent variable is how well they grow.
Hypotheses determine the direction and organization of your subsequent research methods, and that makes them a big part of writing a research paper . Ultimately the reader wants to know whether your hypothesis was proven true or false, so it must be written clearly in the introduction and/or abstract of your paper.
7 examples of hypotheses (with examples)
Depending on the nature of your research and what you expect to find, your hypothesis will fall into one or more of the seven main categories. Keep in mind that these categories are not exclusive, so the same hypothesis might qualify as several different types.
1 Simple hypothesis
A simple hypothesis suggests only the relationship between two variables: one independent and one dependent.
- If you stay up late, then you feel tired the next day.
- Turning off your phone makes it charge faster.
2 Complex hypothesis
A complex hypothesis suggests the relationship between more than two variables, for example, two independents and one dependent, or vice versa.
- People who both (1) eat a lot of fatty foods and (2) have a family history of health problems are more likely to develop heart diseases.
- Older people who live in rural areas are happier than younger people who live in rural areas.
3 Null hypothesis
A null hypothesis, abbreviated as H 0 , suggests that there is no relationship between variables.
- There is no difference in plant growth when using either bottled water or tap water.
- Professional psychics do not win the lottery more than other people.
4 Alternative hypothesis
An alternative hypothesis, abbreviated as H 1 or H A , is used in conjunction with a null hypothesis. It states the opposite of the null hypothesis, so that one and only one must be true.
- Plants grow better with bottled water than tap water.
- Professional psychics win the lottery more than other people.
5 Logical hypothesis
A logical hypothesis suggests a relationship between variables without actual evidence. Claims are instead based on reasoning or deduction, but lack actual data.
- An alien raised on Venus would have trouble breathing in Earth’s atmosphere.
- Dinosaurs with sharp, pointed teeth were probably carnivores.
6 Empirical hypothesis
An empirical hypothesis, also known as a “working hypothesis,” is one that is currently being tested. Unlike logical hypotheses, empirical hypotheses rely on concrete data.
- Customers at restaurants will tip the same even if the wait staff’s base salary is raised.
- Washing your hands every hour can reduce the frequency of illness.
7 Statistical hypothesis
A statistical hypothesis is when you test only a sample of a population and then apply statistical evidence to the results to draw a conclusion about the entire population. Instead of testing everything , you test only a portion and generalize the rest based on preexisting data.
- In humans, the birth-gender ratio of males to females is 1.05 to 1.00.
- Approximately 2% of the world population has natural red hair.
What makes a good hypothesis?
No matter what you’re testing, a good hypothesis is written according to the same guidelines. In particular, keep these five characteristics in mind:
Cause and effect
Hypotheses always include a cause-and-effect relationship where one variable causes another to change (or not change if you’re using a null hypothesis). This can best be reflected as an if-then statement: If one variable occurs, then another variable changes.
Testable prediction
Most hypotheses are designed to be tested (with the exception of logical hypotheses). Before committing to a hypothesis, make sure you’re actually able to conduct experiments on it. Choose a testable hypothesis with an independent variable that you have absolute control over.
Independent and dependent variables
Define your variables in your hypothesis so your readers understand the big picture. You don’t have to specifically say which ones are independent and dependent variables, but you definitely want to mention them all.
Candid language
Writing can easily get convoluted, so make sure your hypothesis remains as simple and clear as possible. Readers use your hypothesis as a contextual pillar to unify your entire paper, so there should be no confusion or ambiguity. If you’re unsure about your phrasing, try reading your hypothesis to a friend to see if they understand.
Adherence to ethics
It’s not always about what you can test, but what you should test. Avoid hypotheses that require questionable or taboo experiments to keep ethics (and therefore, credibility) intact.
How to write a hypothesis in 6 steps
1 ask a question.
Curiosity has inspired some of history’s greatest scientific achievements, so a good place to start is to ask yourself questions about the world around you. Why are things the way they are? What causes the factors you see around you? If you can, choose a research topic that you’re interested in so your curiosity comes naturally.
2 Conduct preliminary research
Next, collect some background information on your topic. How much background information you need depends on what you’re attempting. It could require reading several books, or it could be as simple as performing a web search for a quick answer. You don’t necessarily have to prove or disprove your hypothesis at this stage; rather, collect only what you need to prove or disprove it yourself.
3 Define your variables
Once you have an idea of what your hypothesis will be, select which variables are independent and which are dependent. Remember that independent variables can only be factors that you have absolute control over, so consider the limits of your experiment before finalizing your hypothesis.
4 Phrase it as an if-then statement
When writing a hypothesis, it helps to phrase it using an if-then format, such as, “ If I water a plant every day, then it will grow better.” This format can get tricky when dealing with multiple variables, but in general, it’s a reliable method for expressing the cause-and-effect relationship you’re testing.
5 Collect data to support your hypothesis
A hypothesis is merely a means to an end. The priority of any scientific research is the conclusion. Once you have your hypothesis laid out and your variables chosen, you can then begin your experiments. Ideally, you’ll collect data to support your hypothesis, but don’t worry if your research ends up proving it wrong—that’s all part of the scientific method.
6 Write with confidence
Last, you’ll want to record your findings in a research paper for others to see. This requires a bit of writing know-how, quite a different skill set than conducting experiments.
That’s where Grammarly can be a major help; our writing suggestions point out not only grammar and spelling mistakes , but also new word choices and better phrasing. While you write, Grammarly automatically recommends optimal language and highlights areas where readers might get confused, ensuring that your hypothesis—and your final paper—are clear and polished.

Definition of a Hypothesis
What it is and how it's used in sociology.
- Key Concepts
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A hypothesis is a prediction of what will be found at the outcome of a research project and is typically focused on the relationship between two different variables studied in the research. It is usually based on both theoretical expectations about how things work and already existing scientific evidence.
Within social science, a hypothesis can take two forms. It can predict that there is no relationship between two variables, in which case it is a null hypothesis . Or, it can predict the existence of a relationship between variables, which is known as an alternative hypothesis.
In either case, the variable that is thought to either affect or not affect the outcome is known as the independent variable, and the variable that is thought to either be affected or not is the dependent variable.
Researchers seek to determine whether or not their hypothesis, or hypotheses if they have more than one, will prove true. Sometimes they do, and sometimes they do not. Either way, the research is considered successful if one can conclude whether or not a hypothesis is true.
Null Hypothesis
A researcher has a null hypothesis when she or he believes, based on theory and existing scientific evidence, that there will not be a relationship between two variables. For example, when examining what factors influence a person's highest level of education within the U.S., a researcher might expect that place of birth, number of siblings, and religion would not have an impact on the level of education. This would mean the researcher has stated three null hypotheses.
Alternative Hypothesis
Taking the same example, a researcher might expect that the economic class and educational attainment of one's parents, and the race of the person in question are likely to have an effect on one's educational attainment. Existing evidence and social theories that recognize the connections between wealth and cultural resources , and how race affects access to rights and resources in the U.S. , would suggest that both economic class and educational attainment of the one's parents would have a positive effect on educational attainment. In this case, economic class and educational attainment of one's parents are independent variables, and one's educational attainment is the dependent variable—it is hypothesized to be dependent on the other two.
Conversely, an informed researcher would expect that being a race other than white in the U.S. is likely to have a negative impact on a person's educational attainment. This would be characterized as a negative relationship, wherein being a person of color has a negative effect on one's educational attainment. In reality, this hypothesis proves true, with the exception of Asian Americans , who go to college at a higher rate than whites do. However, Blacks and Hispanics and Latinos are far less likely than whites and Asian Americans to go to college.
Formulating a Hypothesis
Formulating a hypothesis can take place at the very beginning of a research project , or after a bit of research has already been done. Sometimes a researcher knows right from the start which variables she is interested in studying, and she may already have a hunch about their relationships. Other times, a researcher may have an interest in a particular topic, trend, or phenomenon, but he may not know enough about it to identify variables or formulate a hypothesis.
Whenever a hypothesis is formulated, the most important thing is to be precise about what one's variables are, what the nature of the relationship between them might be, and how one can go about conducting a study of them.
Updated by Nicki Lisa Cole, Ph.D
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Children who spend more time playing outside are more likely to be imaginative. What do you think this statement is an example of in terms of scientific research? If you guessed a hypothesis, then you'd be correct. The formulation of hypotheses is a fundamental step in psychology research.
- First, we will discuss the importance of hypotheses in research.
- We will then cover formulating hypotheses in research, including the steps in the formulation of hypotheses in research methodology.
- We will provide examples of hypotheses in research throughout the explanation.
- Finally, we will delve into the different types of hypotheses in research.
What is a Hypothesis?
The current community of psychologists believe that the best approach to understanding behaviour is to conduct scientific research. To be classed as scientific research, it must be observable, valid, reliable and follow a standardised procedure.
One of the important steps in scientific research is to formulate a hypothesis before starting the study procedure.
The hypothesis is a predictive, testable statement predicting the outcome and the results the researcher expects to find.
The hypothesis provides a summary of what direction, if any, is taken to investigate a theory.
In scientific research, there is a criterion that hypotheses need to be met to be regarded as acceptable.
If a hypothesis is disregarded, the research may be rejected by the community of psychology researchers.
Importance of Hypothesis in Research
The purpose of including hypotheses in psychology research is:
- To provide a summary of the research, how it will be investigated, and what is expected to be found.
- To provide an answer to the research question.
When carrying out research, researchers first investigate the research area they are interested in. From this, researchers are required to identify a gap in the literature.
Filling the gap essentially means finding what previous work has not been explained yet, investigated to a sufficient degree, or simply expanding or further investigating a theory if doubt exists.
The researcher then forms a research question that the researcher will attempt to answer in their study.
Remember, the hypothesis is a predictive statement of what is expected to happen when testing the research question.
The hypothesis can be used for later data analysis. This includes inferential tests such as hypothesis testing and identifying if statistical findings are significant.

Steps in the Formulation of Hypothesis in Research Methodology
Researchers must follow certain steps to formulate testable hypotheses when conducting research.
Overall, the researcher has to consider the direction of the research, i.e. will it be looking for a difference caused by independent variables? Or will it be more concerned with the correlation between variables?
All researchers will likely complete the following.
- Investigating background research in the area of interest.
- Formulating or investigating a theory.
- Identify how the theory will be tested and what the researcher expects to find based on relevant, previously published scientific works.
The above steps are used to formulate testable hypotheses.

The Formulation of Testable Hypotheses
The hypothesis is important in research as it indicates what and how a variable will be investigated.
The hypothesis essentially summarises what and how something will be investigated. This is important as it ensures that the researcher has carefully planned how the research will be done, as the researchers have to follow a set procedure to conduct research.
This is known as the scientific method.
Formulating Hypotheses in Research
When formulating hypotheses, things that researchers should consider are:
Types of Hypotheses in Research
Researchers can propose different types of hypotheses when carrying out research.
The following research scenario will be discussed to show examples of each type of hypothesis that the researchers could use. "A research team was investigating whether memory performance is affected by depression."
The identified independent variable is the severity of depression scores, and the dependent variable is the scores from a memory performance task.
The null hypothesis predicts that the results will show no or little effect. The null hypothesis is a predictive statement that researchers use when it is thought that the IV will not influence the DV.
In this case, the null hypothesis would be there will be no difference in memory scores on the MMSE test of those who are diagnosed with depression and those who are not.
An alternative hypothesis is a predictive statement used when it is thought that the IV will influence the DV. The alternative hypothesis is also called a non-directional, two-tailed hypothesis, as it predicts the results can go either way, e.g. increase or decrease.
The example in this scenario is there will be an observed difference in scores from a memory performance task between people with high- or low-depressive scores.
The directional alternative hypothesis states how the IV will influence the DV, identifying a specific direction, such as if there will be an increase or decrease in the observed results.
The example in this scenario is people with low depressive scores will perform better in the memory performance task than people who score higher in depressive symptoms.
Example Hypothesis in Research
To summarise, let's look at an example of a straightforward hypothesis that indicates the relationship between two variables : the independent and the dependent.
If you stay up late, you will feel tired the following day; the more caffeine you drink, the harder you find it to fall asleep, or the more sunlight plants get, the taller they will grow.
Formulation of Hypothesis - Key Takeaways
- The current community of psychologists believe that the best approach to understanding behaviour is to conduct scientific research . One of the important steps in scientific research is to create a hypothesis.
- The hypothesis is a predictive, testable statement concerning the outcome/results that the researcher expects to find.
- Hypotheses are needed in research to provide a summary of what the research is, how to investigate a theory and what is expected to be found, and to provide an answer to the research question so that the hypothesis can be used for later data analysis.
- There are requirements for the formulation of testable hypotheses. The hypotheses should identify and operationalise the IV and DV. In addition, they should describe the nature of the relationship between the IV and DV.
- There are different types of hypotheses: Null hypothesis, Alternative hypothesis (this is also known as the non-directional, two-tailed hypothesis), and Directional hypothesis (this is also known as the one-tailed hypothesis).
Frequently Asked Questions about Formulation of Hypothesis
--> what are the 3 types of hypotheses.
The three types of hypotheses are:
- Null hypothesis
- Alternative hypothesis
- Directional/non-directional hypothesis
--> What is an example of a hypothesis in psychology?
An example of a null hypothesis in psychology is, there will be no observed difference in scores from a memory performance task between people with high- or low-depressive scores.
--> What are the steps in formulating a hypothesis?
All researchers will likely complete the following
- Investigating background research in the area of interest
- Formulating or investigating a theory
- Identify how the theory will be tested and what the researcher expects to find based on relevant, previously published scientific works
--> What is formulation of hypothesis in research?
The formulation of a hypothesis in research is when the researcher formulates a predictive statement of what is expected to happen when testing the research question based on background research.
--> How to formulate null and alternative hypothesis?
When formulating a null hypothesis the researcher would state a prediction that they expect to see no difference in the dependent variable when the independent variable changes or is manipulated. Whereas, when using an alternative hypothesis then it would be predicted that there will be a change in the dependent variable. The researcher can state in which direction they expect the results to go.
Final Formulation of Hypothesis Quiz
What type of hypothesis matches the following definition. A predictive statement that researchers use when it is thought that the IV will not influence the DV.
Show answer
Null hypothesis
Show question
What type of hypothesis matches the following definition. A hypothesis that states that the IV will influence the DV. But, the hypothesis does not state how the IV will influence the DV.
Alternative hypothesis
What type of hypothesis matches the following definition. A hypothesis that states that the IV will influence the DV, and states how it will influence the DV.
Directional, alternative hypothesis
Which type of hypothesis is also known as a two-tailed hypothesis?
What type of hypothesis is the following example. There will be no observed difference in scores from a memory performance task between people with high- or low-depressive scores.
What type of hypothesis is the following example. There will be an observed difference in scores from a memory performance task between people with high- or low-depressive scores.
What type of hypothesis is the following example. People with low depressive scores will perform better in the memory performance task than people who score higher in depressive symptoms.
What is a hypothesis?
The hypothesis is a predictive, testable statement concerning the outcome/ results the researcher expects to find.
What method states that a hypothesis needs to be formulated to produce good research?
The scientific method states that researchers need to formulate a good hypothesis before starting the research.
What steps do researchers need to take when formulating a testable hypothesis?
- Investigating background research in the area of interest
- Formulating or investigating a theory
- Identify how the theory will be tested and what the researcher expects to find based on relevant, previously published scientific works
Why are hypotheses needed in research?
Hypotheses are needed in research:
- to provide a summary of what the researcher is and how investigating a theory and what is expected to be found
- to provide an answer to the research question
- so that the hypothesis can be used for later data analysis
What type of data analysis may hypotheses be needed for?
Hypotheses are needed when doing inferential tests such as hypothesis testing. In addition, identifying if research findings are statistically significant.
What are the requirements of a good hypothesis?
A good hypothesis should:
- identify and operationalise the independent and dependent variable
- be testable
- be falsifiable
- predictive statements
Is the following example a falsifiable hypothesis, "leprechauns always find the pot of gold at the end of the rainbow".
Is memory an operationalised variable that could be used in a good hypothesis?
What is an operationalised variable?
An operationalised variable is when the researcher describes how a variable (independent or dependent variable) will be measured. The operationalisation of variables also needs to be defined. For example, memory may be operationalised by stating performance in memory tasks such as the Mini-Mental Status Examination.
What happens if a hypothesis is regarded as not meeting the standards of scientific research?
If a hypothesis is disregarded, the research may be rejected by the community of psychology researchers.
What is a hypothesis predicting?
The hypothesis predicts the nature of the relationship between the independent and dependent variables. For instance, if the dependent variable changes due to changes/ manipulation of the independent variable.
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Forming a Good Hypothesis for Scientific Research
Kendra Cherry, MS, is an author and educational consultant focused on helping students learn about psychology.
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Verywell / Alex Dos Diaz
- The Scientific Method
Formulating a Hypothesis
Falsifiability, operational definitions, types of hypotheses, examples of hypotheses.
- 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.
For example, a study designed to look at the relationship between sleep deprivation and test performance might have a hypothesis that states, "This study is designed to assess the hypothesis that sleep-deprived people will perform worse on a test than individuals who are not sleep-deprived."
This article explores how a hypothesis is used in psychology research, how to write a good hypothesis, and the different types of hypotheses you might use.
The Hypothesis in the Scientific Method
In the scientific method, whether it involves research in psychology, biology, or some other area, a hypothesis represents what the researchers think will happen in an experiment. The scientific method involves the following steps:
- Forming a question
- Performing background research
- Creating a hypothesis
- Designing an experiment
- Collecting data
- Analyzing the results
- Drawing conclusions
- Communicating the results
The hypothesis is a prediction, but it involves more than a guess. Most of the time, the hypothesis begins with a question which is then explored through background research. It is only at this point that researchers begin to develop a testable hypothesis. Unless you are creating an exploratory study, your hypothesis should always explain what you expect to happen.
In a study exploring the effects of a particular drug, the hypothesis might be that researchers expect the drug to have some type of effect on the symptoms of a specific illness. In psychology, the hypothesis might focus on how a certain aspect of the environment might influence a particular behavior.
Remember, a hypothesis does not have to be correct. While the hypothesis predicts what the researchers expect to see, the goal of the research is to determine whether this guess is right or wrong. When conducting an experiment, researchers might explore a number of factors to determine which ones might contribute to the ultimate outcome.
In many cases, researchers may find that the results of an experiment do not support the original hypothesis. When writing up these results, the researchers might suggest other options that should be explored in future studies.
In many cases, researchers might draw a hypothesis from a specific theory or build on previous research. For example, prior research has shown that stress can impact the immune system. So a researcher might hypothesize: "People with high-stress levels will be more likely to contract a common cold after being exposed to the virus than people who have low-stress levels."
In other instances, researchers might look at commonly held beliefs or folk wisdom. "Birds of a feather flock together" is one example of folk wisdom that a psychologist might try to investigate. The researcher might pose a specific hypothesis that "People tend to select romantic partners who are similar to them in interests and educational level."
Elements of a Good Hypothesis
So how do you write a good hypothesis? When trying to come up with a hypothesis for your research or experiments, ask yourself the following questions:
- Is your hypothesis based on your research on a topic?
- Can your hypothesis be tested?
- Does your hypothesis include independent and dependent variables?
Before you come up with a specific hypothesis, spend some time doing background research. Once you have completed a literature review, start thinking about potential questions you still have. Pay attention to the discussion section in the journal articles you read . Many authors will suggest questions that still need to be explored.
To form a hypothesis, you should take these steps:
- Collect as many observations about a topic or problem as you can.
- Evaluate these observations and look for possible causes of the problem.
- Create a list of possible explanations that you might want to explore.
- After you have developed some possible hypotheses, think of ways that you could confirm or disprove each hypothesis through experimentation. This is known as falsifiability.
In the scientific method , falsifiability is an important part of any valid hypothesis. In order to test a claim scientifically, it must be possible that the claim could be proven false.
Students sometimes confuse the idea of falsifiability with the idea that it means that something is false, which is not the case. What falsifiability means is that if something was false, then it is possible to demonstrate that it is false.
One of the hallmarks of pseudoscience is that it makes claims that cannot be refuted or proven false.
A variable is a factor or element that can be changed and manipulated in ways that are observable and measurable. However, the researcher must also define how the variable will be manipulated and measured in the study.
For example, a researcher might operationally define the variable " test anxiety " as the results of a self-report measure of anxiety experienced during an exam. A "study habits" variable might be defined by the amount of studying that actually occurs as measured by time.
These precise descriptions are important because many things can be measured in a number of different ways. One of the basic principles of any type of scientific research is that the results must be replicable. By clearly detailing the specifics of how the variables were measured and manipulated, other researchers can better understand the results and repeat the study if needed.
Some variables are more difficult than others to define. How would you operationally define a variable such as aggression ? For obvious ethical reasons, researchers cannot create a situation in which a person behaves aggressively toward others.
In order to measure this variable, the researcher must devise a measurement that assesses aggressive behavior without harming other people. In this situation, the researcher might utilize a simulated task to measure aggressiveness.
Hypothesis Checklist
- Does your hypothesis focus on something that you can actually test?
- Does your hypothesis include both an independent and dependent variable?
- Can you manipulate the variables?
- Can your hypothesis be tested without violating ethical standards?
The hypothesis you use will depend on what you are investigating and hoping to find. Some of the main types of hypotheses that you might use include:
- Simple hypothesis : This type of hypothesis suggests that there is a relationship between one independent variable and one dependent variable.
- Complex hypothesis : This type of hypothesis suggests a relationship between three or more variables, such as two independent variables and a dependent variable.
- Null hypothesis : This hypothesis suggests no relationship exists between two or more variables.
- Alternative hypothesis : This hypothesis states the opposite of the null hypothesis.
- Statistical hypothesis : This hypothesis uses statistical analysis to evaluate a representative sample of the population and then generalizes the findings to the larger group.
- Logical hypothesis : This hypothesis assumes a relationship between variables without collecting data or evidence.
A hypothesis often follows a basic format of "If {this happens} then {this will happen}." One way to structure your hypothesis is to describe what will happen to the dependent variable if you change the independent variable .
The basic format might be: "If {these changes are made to a certain independent variable}, then we will observe {a change in a specific dependent variable}."
A few examples of simple hypotheses:
- "Students who eat breakfast will perform better on a math exam than students who do not eat breakfast."
- Complex hypothesis: "Students who experience test anxiety before an English exam will get lower scores than students who do not experience test anxiety."
- "Motorists who talk on the phone while driving will be more likely to make errors on a driving course than those who do not talk on the phone."
Examples of a complex hypothesis include:
- "People with high-sugar diets and sedentary activity levels are more likely to develop depression."
- "Younger people who are regularly exposed to green, outdoor areas have better subjective well-being than older adults who have limited exposure to green spaces."
Examples of a null hypothesis include:
- "Children who receive a new reading intervention will have scores different than students who do not receive the intervention."
- "There will be no difference in scores on a memory recall task between children and adults."
Examples of an alternative hypothesis:
- "Children who receive a new reading intervention will perform better than students who did not receive the intervention."
- "Adults will perform better on a memory task than children."
Collecting Data on Your Hypothesis
Once a researcher has formed a testable hypothesis, the next step is to select a research design and start collecting data. The research method depends largely on exactly what they are studying. There are two basic types of research methods: descriptive research and experimental research.
Descriptive Research Methods
Descriptive research such as case studies , naturalistic observations , and surveys are often used when it would be impossible or difficult to conduct an experiment . These methods are best used to describe different aspects of a behavior or psychological phenomenon.
Once a researcher has collected data using descriptive methods, a correlational study can then be used to look at how the variables are related. This type of research method might be used to investigate a hypothesis that is difficult to test experimentally.
Experimental Research Methods
Experimental methods are used to demonstrate causal relationships between variables. In an experiment, the researcher systematically manipulates a variable of interest (known as the independent variable) and measures the effect on another variable (known as the dependent variable).
Unlike correlational studies, which can only be used to determine if there is a relationship between two variables, experimental methods can be used to determine the actual nature of the relationship—whether changes in one variable actually cause another to change.
A Word From Verywell
The hypothesis is a critical part of any scientific exploration. It represents what researchers expect to find in a study or experiment. In situations where the hypothesis is unsupported by the research, the research still has value. Such research helps us better understand how different aspects of the natural world relate to one another. It also helps us develop new hypotheses that can then be tested in the future.
Castillo M. The scientific method: a need for something better? . AJNR Am J Neuroradiol. 2013;34(9):1669-71. doi:10.3174/ajnr.A3401
Nevid J. Psychology: Concepts and Applications. Wadworth, 2013.
By Kendra Cherry Kendra Cherry, MS, is an author and educational consultant focused on helping students learn about psychology.
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How to Write a Hypothesis

If I [do something], then [this] will happen.
This basic statement/formula should be pretty familiar to all of you as it is the starting point of almost every scientific project or paper. It is a hypothesis – a statement that showcases what you “think” will happen during an experiment. This assumption is made based on the knowledge, facts, and data you already have.
How do you write a hypothesis? If you have a clear understanding of the proper structure of a hypothesis, you should not find it too hard to create one. However, if you have never written a hypothesis before, you might find it a bit frustrating. In this article from EssayPro - custom essay writing services , we are going to tell you everything you need to know about hypotheses, their types, and practical tips for writing them.
Hypothesis Definition
According to the definition, a hypothesis is an assumption one makes based on existing knowledge. To elaborate, it is a statement that translates the initial research question into a logical prediction shaped on the basis of available facts and evidence. To solve a specific problem, one first needs to identify the research problem (research question), conduct initial research, and set out to answer the given question by performing experiments and observing their outcomes. However, before one can move to the experimental part of the research, they should first identify what they expect to see for results. At this stage, a scientist makes an educated guess and writes a hypothesis that he or she is going to prove or refute in the course of their study.
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A hypothesis can also be seen as a form of development of knowledge. It is a well-grounded assumption put forward to clarify the properties and causes of the phenomena being studied.
As a rule, a hypothesis is formed based on a number of observations and examples that confirm it. This way, it looks plausible as it is backed up with some known information. The hypothesis is subsequently proved by turning it into an established fact or refuted (for example, by pointing out a counterexample), which allows it to attribute it to the category of false statements.
As a student, you may be asked to create a hypothesis statement as a part of your academic papers. Hypothesis-based approaches are commonly used among scientific academic works, including but not limited to research papers, theses, and dissertations.
Note that in some disciplines, a hypothesis statement is called a thesis statement. However, its essence and purpose remain unchanged – this statement aims to make an assumption regarding the outcomes of the investigation that will either be proved or refuted.
Characteristics and Sources of a Hypothesis
Now, as you know what a hypothesis is in a nutshell, let’s look at the key characteristics that define it:
- It has to be clear and accurate in order to look reliable.
- It has to be specific.
- There should be scope for further investigation and experiments.
- A hypothesis should be explained in simple language—while retaining its significance.
- If you are making a relational hypothesis, two essential elements you have to include are variables and the relationship between them.
The main sources of a hypothesis are:
- Scientific theories.
- Observations from previous studies and current experiences.
- The resemblance among different phenomena.
- General patterns that affect people’s thinking process.
Types of Hypothesis
Basically, there are two major types of scientific hypothesis: alternative and null.

- Alternative Hypothesis
This type of hypothesis is generally denoted as H1. This statement is used to identify the expected outcome of your research. According to the alternative hypothesis definition, this type of hypothesis can be further divided into two subcategories:
- Directional — a statement that explains the direction of the expected outcomes. Sometimes this type of hypothesis is used to study the relationship between variables rather than comparing between the groups.
- Non-directional — unlike the directional alternative hypothesis, a non-directional one does not imply a specific direction of the expected outcomes.
Now, let’s see an alternative hypothesis example for each type:
Directional: Attending more lectures will result in improved test scores among students. Non-directional: Lecture attendance will influence test scores among students.
Notice how in the directional hypothesis we specified that the attendance of more lectures will boost student’s performance on tests, whereas in the non-directional hypothesis we only stated that there is a relationship between the two variables (i.e. lecture attendance and students’ test scores) but did not specify whether the performance will improve or decrease.
- Null Hypothesis
This type of hypothesis is generally denoted as H0. This statement is the complete opposite of what you expect or predict will happen throughout the course of your study—meaning it is the opposite of your alternative hypothesis. Simply put, a null hypothesis claims that there is no exact or actual correlation between the variables defined in the hypothesis.
To give you a better idea of how to write a null hypothesis, here is a clear example: Lecture attendance has no effect on student’s test scores.
Both of these types of hypotheses provide specific clarifications and restatements of the research problem. The main difference between these hypotheses and a research problem is that the latter is just a question that can’t be tested, whereas hypotheses can.
Based on the alternative and null hypothesis examples provided earlier, we can conclude that the importance and main purpose of these hypotheses are that they deliver a rough description of the subject matter. The main purpose of these statements is to give an investigator a specific guess that can be directly tested in a study. Simply put, a hypothesis outlines the framework, scope, and direction for the study. Although null and alternative hypotheses are the major types, there are also a few more to keep in mind:
Research Hypothesis — a statement that is used to test the correlation between two or more variables.
For example: Eating vitamin-rich foods affects human health.
Simple Hypothesis — a statement used to indicate the correlation between one independent and one dependent variable.
For example: Eating more vegetables leads to better immunity.
Complex Hypothesis — a statement used to indicate the correlation between two or more independent variables and two or more dependent variables.
For example: Eating more fruits and vegetables leads to better immunity, weight loss, and lower risk of diseases.
Associative and Causal Hypothesis — an associative hypothesis is a statement used to indicate the correlation between variables under the scenario when a change in one variable inevitably changes the other variable. A causal hypothesis is a statement that highlights the cause and effect relationship between variables.
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Hypothesis vs Prediction
When speaking of hypotheses, another term that comes to mind is prediction. These two terms are often used interchangeably, which can be rather confusing. Although both a hypothesis and prediction can generally be defined as “guesses” and can be easy to confuse, these terms are different. The main difference between a hypothesis and a prediction is that the first is predominantly used in science, while the latter is most often used outside of science.
Simply put, a hypothesis is an intelligent assumption. It is a guess made regarding the nature of the unknown (or less known) phenomena based on existing knowledge, studies, and/or series of experiments, and is otherwise grounded by valid facts. The main purpose of a hypothesis is to use available facts to create a logical relationship between variables in order to provide a more precise scientific explanation. Additionally, hypotheses are statements that can be tested with further experiments. It is an assumption you make regarding the flow and outcome(s) of your research study.
A prediction, on the contrary, is a guess that often lacks grounding. Although, in theory, a prediction can be scientific, in most cases it is rather fictional—i.e. a pure guess that is not based on current knowledge and/or facts. As a rule, predictions are linked to foretelling events that may or may not occur in the future. Often, a person who makes predictions has little or no actual knowledge of the subject matter he or she makes the assumption about.
Another big difference between these terms is in the methodology used to prove each of them. A prediction can only be proven once. You can determine whether it is right or wrong only upon the occurrence or non-occurrence of the predicted event. A hypothesis, on the other hand, offers scope for further testing and experiments. Additionally, a hypothesis can be proven in multiple stages. This basically means that a single hypothesis can be proven or refuted numerous times by different scientists who use different scientific tools and methods.
To give you a better idea of how a hypothesis is different from a prediction, let’s look at the following examples:
Hypothesis: If I eat more vegetables and fruits, then I will lose weight faster.
This is a hypothesis because it is based on generally available knowledge (i.e. fruits and vegetables include fewer calories compared to other foods) and past experiences (i.e. people who give preference to healthier foods like fruits and vegetables are losing weight easier). It is still a guess, but it is based on facts and can be tested with an experiment.
Prediction: The end of the world will occur in 2023.
This is a prediction because it foretells future events. However, this assumption is fictional as it doesn’t have any actual grounded evidence supported by facts.
Based on everything that was said earlier and our examples, we can highlight the following key takeaways:
- A hypothesis, unlike a prediction, is a more intelligent assumption based on facts.
- Hypotheses define existing variables and analyze the relationship(s) between them.
- Predictions are most often fictional and lack grounding.
- A prediction is most often used to foretell events in the future.
- A prediction can only be proven once – when the predicted event occurs or doesn’t occur.
- A hypothesis can remain a hypothesis even if one scientist has already proven or disproven it. Other scientists in the future can obtain a different result using other methods and tools.
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Now, as you know what a hypothesis is, what types of it exist, and how it differs from a prediction, you are probably wondering how to state a hypothesis. In this section, we will guide you through the main stages of writing a good hypothesis and provide handy tips and examples to help you overcome this challenge:

1. Define Your Research Question
Here is one thing to keep in mind – regardless of the paper or project you are working on, the process should always start with asking the right research question. A perfect research question should be specific, clear, focused (meaning not too broad), and manageable.
Example: How does eating fruits and vegetables affect human health?
2. Conduct Your Basic Initial Research
As you already know, a hypothesis is an educated guess of the expected results and outcomes of an investigation. Thus, it is vital to collect some information before you can make this assumption.
At this stage, you should find an answer to your research question based on what has already been discovered. Search for facts, past studies, theories, etc. Based on the collected information, you should be able to make a logical and intelligent guess.
3. Formulate a Hypothesis
Based on the initial research, you should have a certain idea of what you may find throughout the course of your research. Use this knowledge to shape a clear and concise hypothesis.
Based on the type of project you are working on, and the type of hypothesis you are planning to use, you can restate your hypothesis in several different ways:
Non-directional: Eating fruits and vegetables will affect one’s human physical health. Directional: Eating fruits and vegetables will positively affect one’s human physical health. Null: Eating fruits and vegetables will have no effect on one’s human physical health.
4. Refine Your Hypothesis
Finally, the last stage of creating a good hypothesis is refining what you’ve got. During this step, you need to define whether your hypothesis:
- Has clear and relevant variables;
- Identifies the relationship between its variables;
- Is specific and testable;
- Suggests a predicted result of the investigation or experiment.
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Hypothesis Examples
Following a step-by-step guide and tips from our essay writers for hire , you should be able to create good hypotheses with ease. To give you a starting point, we have also compiled a list of different research questions with one hypothesis and one null hypothesis example for each:
Ask Pros to Make a Perfect Hypothesis for You!
Sometimes, coping with a large academic load is just too much for a student to handle. Papers like research papers and dissertations can take too much time and effort to write, and, often, a hypothesis is a necessary starting point to get the task on track. Writing or editing a hypothesis is not as easy as it may seem. However, if you need help with forming it, the team at EssayPro is always ready to come to your rescue! If you’re feeling stuck, or don’t have enough time to cope with other tasks, don’t hesitate to send us you " rewrite my essay for me " or any other request.
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Crime Analysis for Problem Solvers in 60 Small Steps
Step 20: formulate hypotheses.
Whenever we confront some new and perplexing crime pattern we form hypotheses about its causes, often based on incomplete information. Experience and theory are good sources of hypotheses. You should (1) clearly state your hypotheses, (2) not be wedded to them, and (3) use data to objectively test them. Expect all hypotheses to be altered or discarded once relevant data have been examined because no hypothesis is completely right. For this reason it is often best to test multiple conflicting hypotheses.
A set of hypotheses is a roadmap for analysis. Hypotheses suggest types of data to collect, how this data should be analyzed, and how to interpret analysis results. If you were investigating drinking-related assaults in bars you might begin with the question, "How many bars are problem locations?" Based on the 80-20 rule (Step 18), you would state the hypothesis that some bars will have many fights, but most will have few or none. You would then test this hypothesis by listing the licensed drinking places and counting the number of assault reports at each over the last 12 months.
If your hypothesis was supported, you might ask the question, "What is different about the bars with many fights compared to the bars with few assaults?" The concept of risky facilities (Step 28) would help you form a set of three hypotheses:
- Risky bars have more customers.
- Risky bars have features that attract assaulters.
- Bar staff in risky bars either fail to control behaviors, or provoke fights.
You can test these hypotheses by gathering data on the number of customers at high- and low-risk bars, analyzing the number and rate of assaults per customer, observing the interactions of people at troublesome and trouble-free bars, and interviewing staff and customers.
If your first hypothesis was contradicted by the data, and you found that there was no great difference in numbers of assaults across drinking establishments, then you might ask the question, why are so many bars troublesome? This suggests another hypothesis: It's a perception problem; the city has about as many bar assaults as other comparable cities. This hypothesis suggests that you will need data from comparable cities.
If, after you collected the relevant data, you found that your city has an abnormally high number of problem bars, you might ask the question, "What is common to most bars in the city that produces a large number of assaults?" One hypothesis is that it is the way liquor licenses are dispensed and bars regulated. Another hypothesis is that there is something about the nature of bar customers in your city. Testing each would require you to collect relevant data and assess the validity of the hypothesis.
Notice how the questions and hypotheses structure the analysis. Test results - positive or negative - reveal new, more specific questions. The objective is to start with broad questions and hypotheses and, through a pruning process, come to a set of highly focused questions that point to possible responses.
Hypotheses suggest the type of data to collect. In the bar assaults example, the test of each hypothesis requires specific data. Sometimes the same data can test multiple hypotheses (as is the case with choosing among the three alternative explanations for risky bars). Often a variety of data is required to select among alternative hypotheses (as is the case with the last set of hypotheses). The more specific your hypotheses, the more focused your data collection will be. This is why it is more important to have a clear hypothesis you personally dislike, than an unclear hypothesis you approve of, or worse, no hypothesis at all.
Paralysis by Analysis
The lack of explicit hypotheses can lead to "paralysis by analysis," collecting too much data, conducting too much analysis, and not coming to any useful conclusion.
Hypotheses can help direct the analysis of data. Every clear hypothesis suggests a pattern of data that you should be able to observe, if the hypothesis is correct. In the example above, the hypotheses derived from the concept of risky facilities can be tested using a simple analytical procedure. If a bar is a crime generator, then you should see a high number of assaults, a high number of customers, but a low assault rate (see Step 17). Failure to find this pattern suggests the hypothesis is wrong. So it is important to have a clear idea of what you should observe if your hypothesis is correct, and what you should observe if your hypothesis is wrong (see third column of the table). If you cannot do this, then this is an indicator that your hypothesis may be too vague.
Hypotheses help interpret the analysis results. Let's assume that the analysis of bar fights showed that a few bars had most fights, and observations of the high- and low-risk bars indicated that the security staff of the risky bars provoked fights. This immediately suggests a possible avenue for intervention. In short, the validity of a hypothesis must make a difference. That is, if the hypothesis is true you will take a different decision than if it is false. If you will make the same decision regardless of the test results, then the hypothesis and its test are irrelevant.
In summary, hypotheses are important for guiding analysis. To formulate hypotheses you need to ask important questions, then create simple and direct speculative answers to these questions. These answers are your hypotheses. These speculations must be bold enough that they could be wrong, and there must be a way of showing whether they are right or wrong. If possible, create competing hypotheses.
Hypothesis formation is a useful group exercise, as it allows participants with contrary views to put their perspectives on the table in a way that allows clear and objective tests. In this way, participants contributing invalid hypotheses make substantial contributions to the analysis of the problem. If each hypothesis is linked to a potential solution, the test of these hypotheses simultaneously directs attention to feasible responses and rules out ineffective approaches.
Questions, Hypotheses, and Tests
- Acknowledgements

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Step 3. Formulate your hypothesis. Now you should have some idea of what you expect to find. ...
How to write a hypothesis in 6 steps. 1 Ask a question. Curiosity has inspired some of history’s greatest scientific achievements, so a good place to start is to ask yourself questions ... 2 Conduct preliminary research. 3 Define your variables. 4 Phrase it as an if-then statement. 5 Collect data to ...
Formulating a hypothesis can take place at the very beginning of a research project, or after a bit of research has already been done. Sometimes a researcher knows right from the start which variables she is interested in studying, and she may already have a hunch about their relationships.
The hypothesis can be used for later data analysis. This includes inferential tests such as ...
Steps for Formulating a Hypothesis for an Experiment Step 1: State the question your experiment is looking to answer. Step 2: Identify your independent and dependant variables. Step 3: Write an...
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.
The main sources of a hypothesis are: Scientific theories. Observations from previous studies and current experiences. The resemblance among different phenomena. General patterns that affect people’s thinking process. Types of Hypothesis Basically, there are two major types of scientific hypothesis: alternative and null. Alternative Hypothesis
Hypothesis formation is a useful group exercise, as it allows participants with contrary views to ...