A researcher computes a one-sample z test in two studies. Both studies used the same alpha level, placed the rejection region in both tails, and measured the same sample mean. The researcher selects a sample of 30 participants in Study 1 and decides to retain the null hypothesis. She selects a sample of 60 participants in Study 2 and decides to reject the null hypothesis. Which of the following is the best explanation for why the decision was different in Study 1 and Study 2?
A. The different decisions in Study 1 and Study 2 are not possible because all values were the same.
B. The different decisions in Study 1 and Study 2 are not possible because the researcher tested the same hypothesis.
C. The different decisions in Study 1 and Study 2 are due to an error the researcher made in the first hypothesis test.
D. The different decisions in Study 1 and Study 2 are possible because the second test was associated with greater power to detect an effect.
Ans: D
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