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The null hypothesis attempts to show that no variation exists between variables or that a single variable is no different than its mean.

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The fourth and final step is to analyze the results and either accept or reject the null hypothesis.

Here is a simple example: A school principal reports that students in her school score an average of 7 out of 10 in exams.

This is our situation, so we use a one-tailed test.

We conclude by stating the results of our hypothesis test.

The next step is to formulate an analysis plan, which outlines how the data will be evaluated.

The third step is to carry out the plan and physically analyze the sample data.

We take a random sample of annual returns of the mutual fund for, say, five years (sample) and calculate its mean.

We then compare the (calculated) sample mean to the (claimed) population mean to verify the hypothesis.

To test this “hypothesis,” we record marks of say 30 students (sample) from the entire student population of the school (say 300) and calculate the mean of that sample.

We can then compare the (calculated) sample mean to the (reported) population mean and attempt to confirm the hypothesis.


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