Null Hypothesis
The default assumption in statistical testing that there is no effect or no relationship between the variables being studied.
The null hypothesis, written H0, states that any pattern in the sample data arose by chance: no difference between groups, no association between variables. Statistical tests calculate how likely the observed data would be if the null were true. A small enough p-value leads researchers to reject the null in favor of the alternative hypothesis; otherwise they fail to reject it, which is not the same as proving it true.
In a thesis, precise null hypotheses keep the results chapter honest. They define what each test is actually evaluating, clarify what significance means in your write-up, and prevent the common error of treating a non-significant result as evidence of no effect. Stating them explicitly also helps examiners follow the logic from research question to hypothesis to test to conclusion.
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