Fisher, Neyman-Pearson or NHST? A tutorial for teaching data testing (2015)

Introduction

This paper introduces the classic approaches for testing research data: tests of significance, which Fisher helped develop and promote starting in 1925; tests of statistical hypotheses, developed by Neyman and Pearson (1928); and null hypothesis significance testing (NHST), first concocted by Lindquist (1940). Note: P-values provide information about the theoretical probability of the observed and more extreme results under a null hypothesis assumed to be true (Fisher, 1960; Bakan, 1966), or, said otherwise, the probability of the data given a true hypothesis—P(D|H); (Carver, 1978; Hubbard, 2004). Fisher proposed tests of significance as a tool for identifying research results of interest, defined as those with a low probability of occurring as mere random variation of a null hypothesis.

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