Question

question 3
when do you reject the null hypothesis?
○ a. when the p - value is smaller than a preconceived alpha.
○ b. when the p - value is greater than a preconceived alpha.
○ c. when the p - value is equal to preconceived alpha.

Explanation:

In hypothesis testing, the significance level is denoted by $\alpha$. 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. If the p - value is less than $\alpha$, it means that the observed data is unlikely to have occurred if the null hypothesis is true. So, we reject the null hypothesis. If the p - value is greater than or equal to $\alpha$, we fail to reject the null hypothesis.

Answer:

A. When the p - value is smaller than a preconceived alpha.