Alpha levels are related to confidence levels: to find alpha, just subtract the confidence interval from 100%. for example, the alpha level for a 90% confidence level is 100% – 90% – 10%. To find alpha/2, divide the alpha level by 2.When p value is less than alpha?
Recall that if the p-value is less than alpha in a one-tailed test, this means that the observed statistic lies in the rejection region. The name "rejection" refers to the rejection of the null hypothesis. So if the p-value is less than alpha in a one-tailed test, then the null hypothesis should be rejected. So the answer is C)What is the difference between an alpha level and a p-value?
Alpha, the significance level, is the probability that you will make the mistake of rejecting the null hypothesis when in fact it is true. The p-value measures the probability of getting a more extreme value than the one you got from the experiment. If the p-value is greater than alpha, you accept the null hypothesis.