Question

question 5
what should you do when ( alpha > p \text{-value}? )
○ a. reject ho.
○ b. do not reject ho.

Explanation:

In hypothesis testing, the significance level ($\alpha$) is the probability of rejecting the null hypothesis ($H_0$) when it is true. The p - value is the probability of obtaining a test statistic as extreme or more extreme than the one observed, assuming the null hypothesis is true. When $\alpha>p - value$, it means that the probability of the observed result (or more extreme) under the null hypothesis is less than the pre - set threshold for Type I error ($\alpha$). So, we have sufficient evidence against the null hypothesis.

Answer:

A. Reject $H_0$.