Statistical Power Analysis, 5th Edition

3 Power Analyses for Minimum-Effect Tests

DOI: 10.4324/9781003296225-3

The traditional null hypothesis is that treatments, interventions, etc. have no effect; in Chapters 1 and 2, we used the term “nil hypothesis” to describe this version of H_o. The nil hypothesis is so common and so widely used that most researchers assume that the hypothesis that treatments have no effect, or that the correlation between two variables is zero is the null hypothesis. This is wrong. The null hypothesis is simply the specific hypotheses that is being tested (and that might be nullified by the data), and there are an infinite number of null hypotheses researchers might test. One researcher comparing two treatments might test the hypothesis that there is no difference ...