Classic Topics on the History of Modern Mathematical Statistics: From Laplace to More Recent Times (Repost)

This book presents a clear and comprehensive guide to the history of mathematical statistics, including details on the major results and crucial developments over a 200 year period. The author focuses on key historical developments as well as the controversies and disagreements that were generated as a result. Presented in chronological order, the book features an account of the classical and modern works that are essential to understanding the applications of mathematical statistics. The book begins with extensive coverage of the probabilistic works of Laplace, who laid much of the foundations of later developments in statistical theory. Subsequently, the second part introduces 20th century statistical developments including work from Fisher, Neyman and Pearson. A detailed account of Galton's discovery of regression and correlation is provided, and the subsequent development of Karl Pearson's X2 and Student's t is discussed. Next, the author provides significant coverage of Fisher's works and ultimate influence on modern statistics. The third and final part of the book deals with post-Fisherian developments, including extensions to Fisher's theory of estimation (by Darmois, Koopman, Pitman, Aitken, Fréchet, Cramér, Rao, Blackwell, Lehmann, Scheffé, and Basu), Wald's statistical decision theory, and the Bayesian revival ushered by Ramsey, de Finetti, Savage, and Robbins in the first half of the 20th century.Throughout the book, the author includes details of the various alternative theories and disagreements concerning the history of modern statistics.