When the alternative hypothesis is true, which one of these statements about the power of a significance test is correct?
A) The smaller the difference between the true and null values of a parameter, the larger the power.
B) The power of a test is the probability of a Type 1 error
C) The larger the sample size, the smaller the power of significance test.
D) The power of a test is the probability of not making a Type 2 error

Question

Quizplus · Accepted Answer

The power of a test is indeed the probability of correctly rejecting the null hypothesis when the alternative hypothesis is true, which is equivalent to not making a Type 2 error.

When the Alternative Hypothesis Is True, Which One of These