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.