10 The Implications of Power Analyses
The power of a statistical test is the probability that you will reject the null hypothesis being tested, given that this null hypothesis is wrong. As we have noted throughout this book, the traditional null hypothesis that treatments have no effect whatsoever (or that the correlation between two variables is precisely zero, or any other hypothesis of “no effect”) is very often wrong, and in this context, the statistical power of a test is essentially the probability that the test will lead to the correct conclusion. When testing the traditional null hypothesis, it is obvious that power should always be as high as possible. When testing a minimum-effect hypothesis (e.g., that ...
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