This book offers a detailed history of parametric statistical inference. Covering the period between James Bernoulli and R.A. Fisher, it examines: binomial statistical inference; statistical inference by inverse probability; the central limit theorem and linear minimum variance estimation by Laplace and Gauss; error theory, skew distributions, correlation, sampling distributions; and the Fisherian Revolution. Lively biographical sketches of many of the main characters are featured throughout, including Laplace, Gauss, Edgeworth, Fisher, and Karl Pearson. Also examined are the roles played by DeMoivre, James Bernoulli, and Lagrange.
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From the reviews:
"In this very enjoyable and interesting book, Hald ... presents his subject in a very lively style; many ideas and developments in statistics are treated with great clarity. It is very suitable as a course resource in history of statistical inference ... . Throughout, the author provides brief biographical sketches of researchers whose contributions to statistics are included here. ... A very useful and valuable work on the history of statistical inference. ... Summing Up: Highly recommended. Lower- and upper-division undergraduates through faculty." (D. V. Chopra, CHOICE, Vol. 44 (11), July, 2007)
"This is a useful account of the historical development of the theory that underlies the empirically observed stability of data averages for large samples and how their precision may be measured. ... The resultant book is a suitable text for a one-semester course on what is arguably the core piece of statistical history." (C. C. Heyde, SIAM Review, Vol. 50 (1), 2008)
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