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Neyman–Pearson theory

an approach to formulating two competing hypotheses (the null hypothesis and an alternative hypothesis) and identifying appropriate statistical procedures for choosing between them. It focuses on identifying critical regions, minimizing errors in estimation, and obtaining an appropriate balance in the probability of committing Type I errors and Type II errors. [Jerzy Neyman (1894–1981), Russian-born U.S. statistician; Egon S. Pearson (1895–1980), British statistician]

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