Explanation:
The power of a test is the probability of correctly rejecting a false null hypothesis, which is a key concept in hypothesis testing. It is distinct from the p-value (the smallest significance level for rejecting the null) and the level of significance (the probability of a Type I error). Understanding these components is essential for interpreting hypothesis test results.
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The probability of correctly rejecting a false null hypothesis is best defined as the:
A
p-value, which represents the smallest level of significance at which the null hypothesis can be rejected.
B
power of the test, which is the probability of correctly rejecting the null hypothesis when it is false.
C
level of significance, which is the probability of rejecting a true null hypothesis (Type I error).
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