Blackwell Reference Online

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The history of statistical hypothesis testing is, indeed, very long. Neyman and Pearson (1933) traced its origin to Bayes (1763) . However, systematic applications of hypothesis testing began only after the publication of Karl Pearson's (1900) goodness-of-fit test, which is regarded as one of the 20 most important scientific breakthroughs in this century. In terms of the development of statistical methods, Ronald Fisher took up where Pearson left off. Fisher (1922) can be regarded as the analytical beginning of statistical methods. In his paper Fisher advocated the use of maximum likelihood estimation and provided the general theory of parametric statistical inference. In order to develop various statistical techniques, Fisher (1922) also introduced such basic concepts as consistency, efficiency, and sufficiency that are now part of our day-to-day vocabulary. Fisher, however, was not particularly interested in testing per se , and he occupied himself mostly in solving problems of estimation and sampling distributions. Neyman and Pearson (1928) suggested the likelihood ratio (LR) test, but that was mostly based on intuitive arguments. The foundation of the theory of hypothesis testing was laid by Neyman and Pearson (1933) , and for the first time the concept of “optimal test” was introduced through the analysis of “power function.” The result was the celebrated Neyman-Pearson ... log in or subscribe to read full text