When the conventional 0.05 significance level is used to analyze listening test data, employing a small number of trials or listeners can produce an unexpectedly high risk of concluding that audible differences are inaudible (type 2 error). The risk can be both large absolutely and large relative to the risk of concluding that inaudible differences are audible (type 2 error). this constitutes systematic bias against those who believe that differences are audible between well-designed electronic components that are spectrally equated and not overdriven. A statistical table is introduced that enables readers to look up type 1 and type 2 error risks without calculation. Ways to manipulate the risks are discussed, a quantitative measure of a listening test's fairness is introduced, and implications for reviewers of the listening test literature are discussed.
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