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
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.
The seven types of hypotheses are listed below:5,6,7
Example: Exercising in the morning every day will increase your productivity.
Example: Spending three hours or more on social media daily will negatively affect children’s mental health and productivity, more than that of adults.
Example: The inclusion of intervention X decreases infant mortality compared to the original treatment.
Example: Cats and dogs differ in the amount of affection they express.
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.
Example: Sleep duration does not have any effect on productivity.
Example: Sleep duration affects productivity.
So, what makes a good hypothesis? Here are some important characteristics of a hypothesis.8,9
The following list mentions some important functions of a hypothesis:1
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
Listed below are the main steps explaining how to write a hypothesis.2,4,5
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.
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?”
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.
Population: The specific group or individual who is the main subject of the research
Interest: The main concern of the study/research question
Comparison: The main alternative group
Outcome: The expected results
Time: 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.
The following table provides examples of different types of hypotheses.10,11
| Type | Example |
| Null | Hyperactivity is not related to eating sugar. |
| There is no relationship between height and shoe size. | |
| Alternative | Hyperactivity is positively related to eating sugar. |
| There is a positive association between height and shoe size. | |
| Simple | Students who eat breakfast perform better in exams than students who don’t eat breakfast. |
| Reduced screen time improves sleep quality. | |
| Complex | People with high-sugar diet and sedentary activity levels are more likely to develop depression. |
| 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. | |
| Directional | As job satisfaction increases, the rate of employee turnover decreases. |
| Increase in sun exposure increases the risk of skin cancer. | |
| Non-directional | College students will perform differently from elementary school students on a memory task. |
| Advertising exposure correlates with variations in purchase decisions among consumers. | |
| Associative | Hospitals have more sick people in them than other institutions in society. |
| Watching TV is related to increased snacking. | |
| Causal | Inadequate sleep decreases memory retention. |
| Recreational drugs cause psychosis. |
Key takeaways
Here’s a summary of all the key points discussed in this article about how to write a hypothesis.
Hypotheses and research questions have different objectives and structure. The following table lists some major differences between the two.9
| Hypothesis | Research question |
| Includes a prediction based on the proposed research | No prediction is made |
| Designed to forecast the relationship of and between two or more variables | Variables may be explored |
| Closed ended | Open ended, invites discussion |
| Used if the research topic is well established and there is certainty about the relationship between the variables | Used for new topics that haven’t been researched extensively. The relationship between different variables is less known |
Here are a few examples to differentiate between a research question and hypothesis.
| Research question | Hypothesis |
| What is the effect of eating an apple a day by adults aged over 60 years on the frequency of physician visits? | Eating an apple each day, after the age of 60, will result in a reduction of frequency of physician visits |
| What is the effect of flexible or fixed working hours on employee job satisfaction? | Workplaces that offer flexible working hours report higher levels of employee job satisfaction than workplaces with fixed hours. |
| Does drinking coffee in the morning affect employees’ productivity? | Drinking coffee in the morning improves employees’ productivity. |
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 H0, 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 H1, 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
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