Type I, II Error
For a hypothesis test with a probability of a Type II error of 60% and a
probability of a Type I error of 5%, which of the following statements is most
A. The power of the test is 40%. and there is a 5% probability that the test
statistic will exceed the critical value(s).
B. There is a 95% probability that the test statistic will be between the critical
values if this is a two-tailed test.
C. There is a 5% probability that the null hypothesis will be rejected when
actually true. and the probability of rejecting the null when it is false is
They claim that the answer is C, on the basis that in A,B the null hypothesis could be false, which would make the claims invalid in options (A,B) since the probability of rejection would be unknown.
How does this make sense? I do not get their reasoning. Is the probability of rejecting the null hypothesis already incorporated into the probabilities?
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