What increases the power of a test? Check all that apply.increasing the sample size and significance leveldecreasing the sample size and significance leveltrying to detect a value close to the hypothesized valuetrying to detect a value far from the hypothesized valueincreasing the probability of a Type II errordecreasing the probability of a Type II error
Answer
A
increasing the sample size and significance level
B
decreasing the sample size and significance level
C
trying to detect a value close to the hypothesized value
D
trying to detect a value far from the hypothesized value
E
increasing the probability of a Type II error
F
decreasing the probability of a Type II error
Explanation
A test’s power is the probability of rejecting the null hypothesis when it is false. Increasing the sample size or significance level generally increases power, so A applies. Power is greater when the true value is farther from the hypothesized value, and decreasing the probability of a Type II error (β) increases power because power equals 1 − β; therefore D and F apply.
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