1. Let's restate the problem: We need to perform hypothesis testing as asked in part bi) with more detailed explanation of the steps. 2. Define the null hypothesis ($H_0$) and the alternative hypothesis ($H_a$). 3. Choose a significance level ($\alpha$), often 0.05. This represents the probability of rejecting $H_0$ when it is actually true. 4. Calculate the test statistic based on your sample data. The formula depends on the test type (e.g., z-test, t-test). 5. Determine the critical value(s) from statistical tables corresponding to $\alpha$. 6. Compare the test statistic to the critical value: - If the test statistic falls in the rejection region, reject $H_0$. - Otherwise, fail to reject $H_0$. 7. Draw a conclusion in the context of the problem based on the results. This structured approach ensures we carefully assess the evidence from the sample data against our hypothesis.