When planning an experiment, Neyman and Pearson suggested that we should choose two quantities which together will determine how large the experiment should be. First, we should fix the probability of a Type I error, given the null is true, at a pre-specified value, say 0.05; this is known as the size of a test, and generally denoted α (alpha). Second, we should pre-specify the probability of a Type II error, given the alternative hypothesis is true, generally known as β (beta). In fact researchers generally work in terms of 1 – β, which is termed the power of a test, and is the chance of
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