Updated December 26, 2023
Meaning
A research hypothesis is a statement that a researcher makes at the beginning of their research to outline what they expect the outcome to be.
Example:
If the hypothesis is “More air pollution in an area can lead to more respiratory diseases,” researchers expect that an increase in air pollution will cause more respiratory diseases in that area.
This hypothesis is needed because it provides focus, structure, and purpose to research, helping researchers test their ideas and make meaningful conclusions based on evidence gathered during their study.
Table of Content
- Meaning
- Types and Examples
- Characteristics
- Importance
- How to Write a Research Hypothesis?
- How to Test a Research Hypothesis? (with Example)
- Advantages and Disadvantages
- Research vs. Null vs. Statistical Hypothesis
Key Highlights
- Researchers need to develop a research hypothesis for their study to specify its direction and expectations.
- The main difference between a research hypothesis and a null hypothesis is that while a research hypothesis emphasizes the existence of a relationship between variables, a null hypothesis denies it.
- On the other hand, the main difference between a statistical and a research hypothesis is that while a research hypothesis states the relationship between any two or more variables, the statistical hypothesis only talks about the mathematical relationship of a population parameter.
Types
Here’s a snapshot to help you differentiate between all types of research hypothesis easily.
Detailed explanation of each type is as follows:
1. Simple Hypothesis
This type looks at how two variables might be related to each other. These variables are the dependent variable and independent variable. A dependent variable is a factor that changes with the changes in the independent variable.
Example of Simple Hypothesis:
Suppose you want to study the relationship between studying for long hours and grades. In this relationship, grades are the dependent variable, and hours of study are the independent variable, as getting a high or low grade depends on how much you study. And your simple hypothesis could be: “More study time leads to higher grades.”
2. Complex Hypothesis
Unlike the simple hypothesis, a complex hypothesis predicts a relationship between multiple variables.
Example of Complex Hypothesis:
Imagine you want to understand how sleep, diet, and exercise affect health. In this case, you have one dependent variable, health, and three independent variables – sleep, diet, and exercise. Your complex hypothesis can be something like: “A combination of enough sleep, a balanced diet, and regular exercise positively impacts overall health.“
3. Null Hypothesis
This hypothesis assumes no relationship between variables. It is a negative statement. It’s usually the opposite of your actual hypothesis.
Example of Null Hypothesis:
Suppose you are studying whether shoe size affects intelligence; the null hypothesis would say: “There is no association between shoe size and intelligence.“
4. Alternative Hypothesis
This is the opposite of the null hypothesis. It is a statement specifying a relationship between variables.
Example of Alternative Hypothesis:
Suppose you are researching the effect of water intake on memory. An alternative hypothesis could be: “Increased water intake improves memory performance.“
5. Directional Hypothesis
A directional hypothesis predicts the specific direction or nature of the relationship between two or more variables.
Example of Directional Hypothesis:
Let’s say you want to investigate the effect of practicing an instrument on musical skills. A directional hypothesis could be something like: “Increased practice time improves musical skill.” In this case, it is clear how one variable impacts the other.
6. Non-directional Hypothesis
In a non-directional hypothesis, a researcher states that two variables are related but doesn’t specify how.
Example of Non-directional Hypothesis:
Suppose you are researching the relationship between caffeine intake and heart rate. A non-directional hypothesis might state: “There is a relationship between caffeine intake and heart rate.” This hypothesis doesn’t tell you if caffeine intake affects the heart rate or if the heart rate affects your caffeine intake.
7. Associative Hypothesis
This hypothesis focuses on a relationship between variables but doesn’t claim that one causes the other.
Example of Associative Hypothesis:
Imagine you want to study if TV watching and increased snacking are related. An associative hypothesis might state: “Watching more TV is related to increased snacking.”
8. Causal Hypothesis
On the other hand, a causal hypothesis suggests that the changes in one thing directly cause changes in another.
Example of Causal Hypothesis:
If you are studying sunlight exposure and vitamin D levels, a causal hypothesis could be: “Lack of sunlight exposure causes vitamin D deficiency.“
Characteristics
A research hypothesis should have the following characteristics:
- Simple and Clear: A good research hypothesis should make sense, be believable, and be based on past research.
- Testability: It should be something that can be tested in real life through scientific methods like experiments or observations.
- Realistic: Your research hypothesis can’t be unrealistic or restricted by current technology.
- Proven or Disproven: Your research should either prove or disprove your research hypothesis.
- Precise and Logical: Your hypothesis should clearly state what you are trying to find out and achieve through your research. Make a declarative statement that is logical and easy to understand.
- Relationship: Your hypothesis should clearly define the factors or variables being studied and explain how they are connected.
- Further Investigations: The hypothesis should encourage future studies and experiments by keeping doors open for additional research.
Importance
It’s important for research to have a research hypothesis because of the following reasons:
- To direct the research: A hypothesis acts like a map, telling researchers where to go and what to explore during their study. It helps in focusing on specific questions.
- Provides structure and focus: It gives a clear structure to the research by defining what needs to be tested. It prevents the research from becoming disorganized.
- Adds specificity: By stating what researchers expect to find, it makes the study more specific, avoiding confusion. A research hypothesis keeps the research on track.
- Helps to draw conclusions: It assists in drawing meaningful conclusions based on evidence gathered during the research. This helps the researchers to understand and explain their findings.
- Saves time and resources: Developing a hypothesis at the beginning of the research helps in efficiently using resources by concentrating efforts on what’s important.
How to Write a Research Hypothesis?
Below is the step-by-step guide to writing a research hypothesis.
Step 1. Find your research question.
Start by identifying what you want to research. Say, for instance, you are interested in understanding the relationship between AI and Productivity; this will form the basis of your research question. Your research question could be:
Step 2. Identify your variables
In the above example, the two variables are AI integration and employee productivity. Now, define which variable is dependent and which one is independent. The independent variable is the one you think will influence, and the dependent variable is the one that will be influenced.
Dependent variable: Employee productivity
Step 3: Conduct preliminary research
Before you formulate your research hypothesis, you need to find out what past research on this subject is saying. This will help you understand what direction your research might take.
Step 4. Formulate your hypothesis
Based on past research, you can now write a clear and specific statement predicting how your dependent and independent variables are connected. Now, write down your research and null hypothesis.
Null hypothesis: AI integration has no impact on employee productivity.
How to Test a Research Hypothesis?
Once you have developed your alternative/research and null hypothesis, your next task is to test your research hypothesis. Here’s how you do that:
1. Create a Research Plan
Decide how you will gather information or conduct experiments to test your hypothesis. Determine what tools or methods you will use, the research population, the research sample, sample size, etc.
2. Collect Data
Carry out your experiments or observations and gather data related to your hypothesis. For example, if you are studying the impact of study time on grades, write down how many hours each student participating in your research spends on studying and the grades they get.
3. Analyze the Data
Use statistical tools or other analysis methods to study the collected data.
4. Draw Conclusions
Based on your analysis, determine if the evidence supports your hypothesis. If the data backs up your prediction, your hypothesis is supported.
5. Communicate Findings
Share your results with others through reports or presentations, explaining how your experiments or observations relate to your hypothesis.
Example:
Let’s take the example of Dr. Lily Perry, a researcher from New York City. She wants to investigate if there is a relationship between respiratory diseases and air pollution in New York.
She starts by creating her research hypothesis and null hypothesis.
Null hypothesis: No correlation exists between air pollution levels and respiratory diseases in New York.
Dr. Perry followed a detailed plan to do her research:
- She checked the air quality in different parts of the city for three years (2020 to 2023) to understand how it affects people’s breathing.
- During this period, she went to many hospitals in New York and checked the medical records of patients with respiratory illnesses.
- Finally, Dr. Perry studied the information she collected and considered factors like age, gender, and money to learn more about respiratory health.
After an intensive three-year study, Dr. Perry found interesting results:
- Areas with high pollution levels had 30% more asthma patients than areas with cleaner air.
- For instance, in one neighborhood with high air pollution, the number of people with asthma increased from 100 to 130 out of 10,000.
- However, in a neighborhood with low levels of air pollution, the patient count remained at 80 out of 10,000.
Based on these results, Dr. Perry concluded that:
There is a correlation between increased air pollution and respiratory diseases in New York.
She recommended the following:
- To reduce air pollution levels, government authorities should improve public transportation.
- People living in polluted areas can use face masks and air purifiers.
- When air quality is extremely bad, authorities should warn citizens to avoid outdoor activities.
- Encourage planting more trees as it can have long-term benefits.
- To reduce pollution levels, authorities should promote the use of electric vehicles more.
Advantages and Disadvantages
Following are the main advantages and disadvantages of a research hypothesis
| Advantages | Disadvantages |
| It gives your research a specific direction. | It can stop you from exploring all aspects of the study. |
| It helps you predict the outcome of your study. | It can cause bias as you already have an outcome in mind. |
| It assists in finding an appropriate data collection method. | You might need to revise your hypothesis based on the results of the study. |
Research vs. Null vs. Statistical Hypothesis
The following are the main differences between research, null, and statistical hypothesis.
| Aspects | Research Hypothesis | Null Hypothesis | Statistical Hypothesis |
| Meaning | States the expected relationship between two or more variables. | Assumes there is no relationship between the variables involved in a study. | A mathematical explanation of the relationship between variables. |
| Example | Individuals exercising regularly have a lower risk of heart disease. | There is no link between exercise and heart diseases. | Individuals exercising regularly have a lower resting heart rate than those who do not. |
| Purpose | To prove a certain relationship exists between the variables. | To prove the variables are not related to each other. | To be proven using statistical methods. |
| Direction | Usually states how two variables are related. | Has no direction and emphasizes there is no correlation. | Could be directional as well as non-directional based on the context. |
| Role in testing | Needs to be tested through statistical and non-statistical methods. | Assumed true until disproven by research. | Is tested with statistical methods. |
Final Thoughts
Formulating a research hypothesis is usually the first step in conducting any research. However, it is important to know that your hypothesis might be disproven on occasion as well. The purpose of the research is to determine if your predictions about a specific relationship hold in light of evidence.
Frequently Asked Questions (FAQs)
Q1. How long should a research hypothesis be?
Answer: A good research hypothesis should be just one or two sentences. For example: Increasing the amount of water that a cucumber plant receives will lead to increased production.
Q2. Where do you put the hypothesis in a research paper?
Answer: In the research paper, the hypothesis is usually placed after the introduction section. The introduction section is added after the background section and before the research methodology.
Q3. What is the research hypothesis when using ANOVA procedures?
Answer: To understand this concept, let’s use an example. Let’s say you want to investigate whether there is a difference in the average marks of students in four different divisions. For this, you can use ANOVA (it helps determine if there is a significant difference between the means of three or more samples).
So, your research hypothesis would be: There is a difference in the average scores of students in the four divisions.
Your null hypothesis would be: There is no difference in the average scores of students in the four divisions.
To test these hypotheses, you would collect data (marks of the students) from the four divisions. You would then analyze the data using ANOVA and determine whether you should accept the research hypothesis and reject the null hypothesis or vice versa.
Q4. Does qualitative research or descriptive research have a hypothesis?
Answer: Qualitative and descriptive research typically do not have a hypothesis. Instead, they have research questions to help the researcher conduct a detailed analysis.
Examples of research questions:
- What are the challenges faced by new mothers during postpartum?
- What are the views of employees towards work-from-home during COVID-19?
Q5. What is the difference between a research hypothesis and a research question?
Answer: A research question is what you want to explore, while a research hypothesis is what you expect the outcome of the study to be.
Q6. What is an example of a good and a bad hypothesis?
Answer: “Increased exercise leads to improved heart health” is an example of a strong hypothesis as it predicts a clear relationship between variables. Furthermore, it is possible to test the hypothesis. On the other hand, “Apples are better than oranges” is an example of a bad or poor hypothesis as it is a subjective statement and can’t be tested.
