Hypothesis is an informed guess or forecast. This prediction will be directly tested in your dissertation research. Hypotheses are found in the majority of quantitative research such as science and psychology. Research questions are usually used in qualitative research. Knowing this difference is a time-saving step in the future. A research hypothesis for dissertation gives you good guidance throughout your research.
It informs the readers of what they are about to read. This tutorial will take you through the process of writing testable, specific hypotheses that will make your dissertation stronger. You should know how you are going to research before you write your hypothesis. Find out what is the distinction between qualitative vs quantitative research to decide the appropriate direction to follow in your research.
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The Null vs. Alternative Hypothesis (H0 vs. H1)
Statistical tests are based on two conflicting hypotheses. Both are critical to dissertation writing.
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Null Hypothesis (H0)
The null hypothesis is that there is no association between variables. It is the null hypothesis that is attempted to be refuted by research. As an example, “Coffee does not impact the duration of sleep. The null hypothesis indicates that any effect that is observed is solely due to chance. The researchers want to disapprove the null hypothesis at great length.
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Alternative Hypothesis (H1)
The other hypothesis is a prediction of a particular correlation between variables. It is what you would hope to find. As an illustration, “Coffee reduces overall sleep time by 30 minutes or more. The null hypothesis is directly opposite to the alternative hypothesis. This means that your data will either support or reject the null or the alternative.
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Testing the Null
We attempt to reject the null hypothesis, statistically. The alternative hypothesis is never actually proved. Rather, we accept the null at a confidence level. This is initially confusing to hear. Nonetheless, it is a basic rule of statistical testing. These null and alternative hypothesis examples demonstrate how to word either statement. Proper statistical testing of each dissertation hypothesis needs both versions.
Your problem statement should come before your hypothesis. Get to know what is a problem statement and how to write a good problem statement in your dissertation.
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Structuring Your Hypothesis (Variables)
Each hypothesis has to have a connection between two kinds of variables. It is this relationship that is at the base of any testable research prediction. Your hypothesis can not be tested correctly without clear identification of the variables.
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Independent Variable (Cause)
Manipulation or change is the independent variable. It is the presumed cause in your study. An example of an independent variable is, say, daily social media usage. You could compare various levels of usage among groups. This variable is actively controlled or chosen by researchers. It is not subject to anything in the study. You can consider it the “input” that you can modify to observe the results. The independent variable you select should be given a lot of consideration in regards to the research question.
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Dependent Variable (Effect)
What you measure as the outcome is the dependent variable. The supposed influence of your influence. Anxiety scores on a standardized scale, e.g., is a dependent variable. The level of influence of the independent variable on this outcome is predicted by your hypothesis. This variable depends on what the participant does or experiences. It is the output that you measure following the application of your independent variable. The dependent variable has to vary depending on the independent variable.
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Be Specific and Testable
Avoid such general terms as bad effect, influences. Change what and by what percentage. As an illustration, “reduces the test scores by 10 percent. Note: also make sure that you are able to measure all the variables. And when you are unable to measure something, you are unable to test it. Understanding how to write a hypothesis means mastering this specificity. Use numbers and scales whenever possible. Name the specific measurement tool you will use.
The time you write your hypotheses is during your proposal. Develop a strong research proposal that contains clear and testable hypotheses at the outset.
Examples of Strong vs. Weak Hypotheses
Weak dissertations are caused by weak hypotheses. Powerful hypotheses will cause cogent data analysis and will result in research findings that are meaningful and defensible.
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Weak Hypothesis Example
“Social media is bad for mental health.”
This statement does not work at all as a hypothesis. It involves the use of ambiguous words such as bad. It does not indicate what social media platform. It fails to specify mental health measures. It does not provide any guidelines in statistical testing. This structure is to be avoided.
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Strong Hypothesis Example
“Daily social media usage exceeding three hours correlates with higher anxiety scores on the GAD-7 scale among UK teenagers aged 13 to 17.”
This is a good hypothesis. It defines the independent variable (daily use more than three hours). It refers to the dependent variable (GAD-7 anxiety scores). It identifies the population (teenagers in the UK between the age of 13 and 17). It contains quantifiable terms. Such clarity facilitates easy testing.
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Why Specificity Matters
Vague hypotheses yield smoking results. A fuzzy statement is something that you cannot either prove or disprove. Good hypotheses give straight forward conclusions. Even a strong hypothesis, which turns out to be false, teaches you something good.
Your methodology for dissertation requires you to have testable hypotheses in the beginning. To know how to match your research design with your hypothesis structure, visit our methodology to guide you on doing a dissertation.
Conclusion
Composing a good research hypothesis is a practice. Begin with a definite forecast regarding the relationships between variables. Spell out null and alternative forms. Be precise and quantitative. Do not use general expressions such as bad or influences. Do not forget that it is still valid research to prove your hypothesis wrong. Emphasize testability and clarity first of all.
A structured hypothesis is what helps to direct your whole dissertation to significant conclusions. Read and re-read your draft. Early feedback: Request your supervisor to provide you with feedback. Make changes according to their recommendations. Good dissertations are based on good hypotheses. Be willing to spend time getting yours at the start.
