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) accepting a true null hypothesis, accepting a false null hypothesis, or rejecting a true null hypothesis, depending on the situation

Question

Quizplus · Accepted Answer

The level of significance (often denoted as alpha) in hypothesis testing is the probability of rejecting a true null hypothesis. This means that if the level of significance is 0.05, then there is a 5% chance of incorrectly rejecting a null hypothesis that is actually true. Choosing A or D is incorrect because they both involve accepting a true null hypothesis, which is not affected by the level of significance. Choice B is incorrect because the level of significance does not account for accepting a false null hypothesis; that is determined by the errors in testing.

The Level of Significance in Hypothesis Testing Is the Probability