Egon Pearson

Egon Pearson was a British statistician who, working closely with the Polish mathematician Jerzy Neyman during the 1920s and 1930s, developed a rigorous mathematical framework for statistical hypothesis testing that remains one of the central pillars of modern applied statistics. Their joint result, now known as the Neyman-Pearson lemma, provided a precise mathematical procedure for deciding, in a given testing situation, which possible statistical test is the single most powerful one available for correctly distinguishing between two competing hypotheses while keeping the risk of a false positive result fixed at some chosen acceptable level. This work, together with the broader Neyman-Pearson framework of hypothesis testing they built around it, introduced concepts, including the formal distinction between a false positive and a false negative error, that became standard vocabulary used across virtually every scientific field that relies on statistical testing of experimental or observational data. Pearson was the son of the pioneering statistician Karl Pearson, whom he eventually succeeded as professor of statistics and head of the statistics department at University College London, and he served for many years as editor of the statistical journal Biometrika, a position his father had also once held. Pearson later served as president of the Royal Statistical Society and was elected a Fellow of the Royal Society in recognition of his foundational contributions to statistical theory.