Question

The is the probability of rejecting the null hypothesis when it is in fact false and should be rejected.

• A. type I error
• B. level of significance
• C. type II error
• D. power of a test

Hint:

High power = high probability of detecting a true effect when it exists.

Answer 1

The Correct Option is D

Step 1: Key definition.
The power of a test is $1 - \beta$, the probability of correctly rejecting a false $H_0$.
Step 2: Eliminate distractors.
(a) Type I error is $\alpha$, rejecting a true $H_0$.
(b) Level of significance $\alpha$ is the threshold for rejecting $H_0$.
(c) Type II error $\beta$ is failing to reject a false $H_0$. \[ \boxed{(d)} \]