The level of significance in hypothesis testing is the probability of
A)accepting a true null hypothesis
B)accepting a false null hypothesis
C)rejecting a true null hypothesis
D)could be any of the above, depending on the situation

Question

Quizplus · Accepted Answer

The level of significance in hypothesis testing is the probability of rejecting a true null hypothesis. It represents the maximum probability of making a Type I error (i.e., rejecting a null hypothesis when it is actually true). Accepting a true null hypothesis would be correct, and accepting a false null hypothesis would be a Type II error. The level of significance cannot be any of the above, as it is a specific concept with a defined meaning.

The Level of Significance in Hypothesis Testing Is the Probability