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Originally published: New York: John Wiley & Sons, Inc., 2001.
The present volume represents the Proceedings of an International Research Seminar organized in 1963 by the Statistical Laboratory, Uni versity of California, Berkeley, on the occasion of a remarkable triple anniversary: the 250th anniversary of jACOB BERNOULLI's "Ars Conjectandi", the 200th anniversary of THOMAS BAYES' "Essay towards solving a problem in doctrine of chance", and the!50th anniversary of the PIERRE-SIMON DE LAPLACE's "Essai philosophique sur les probabilites". Financial assistance of the National Science Foundation, without which the Seminar could not have been held, is gratefully acknowledged. The publication of Ars Conjectandi, in 1713, was a milestone in the history of probability theory. Here, for the first time, appeared a careful description of the now well-known combinatorial methods which give solutions of many problems on simple games of chance. Also, Ars Conjectandi contains the Bernoulli numbers, theorems relating to the duration of games, and to the ruin of gamblers and, above all, the state ment and proof of the famous Bernoulli weak law of large numbers. Even though the original Latin edition of Ars Conjectandi was followed by several in modern languages, currently the book is not easily accessible. Apparently the last re-publication, in German, occurred in 1899, in two issues, No. 107 and No. 108, of the series "Ostwald's Klassi ker der exakten Wissenschaften", Wilhelm Engelman, Leipzig. The two books are difficult to locate
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.
1963 Anniversary Volume
A world list of books in the English language.
The long-awaited second volume of Anders Hald's history of the development of mathematical statistics. Anders Hald's A History of Probability and Statistics and Their Applications before 1750 is already considered a classic by many mathematicians and historians. This new volume picks up where its predecessor left off, describing the contemporaneous development and interaction of four topics: direct probability theory and sampling distributions; inverse probability by Bayes and Laplace; the method of least squares and the central limit theorem; and selected topics in estimation theory after 1830. In this rich and detailed work, Hald carefully traces the history of parametric statistical inference, the development of the corresponding mathematical methods, and some typical applications. Not surprisingly, the ideas, concepts, methods, and results of Laplace, Gauss, and Fisher dominate his account. In particular, Hald analyzes the work and interactions of Laplace and Gauss and describes their contributions to modern theory. Hald also offers a great deal of new material on the history of the period and enhances our understanding of both the controversies and continuities that developed between the different schools. To enable readers to compare the contributions of various historical figures, Professor Hald has rewritten the original papers in a uniform modern terminology and notation, while leaving the ideas unchanged. Statisticians, probabilists, actuaries, mathematicians, historians of science, and advanced students will find absorbing reading in the author's insightful description of important problems and how they gradually moved toward solution.
There is currently no viable alternative to the Bayesian analysis of scientific inference, yet the available versions of Bayesianism fail to do justice to several aspects of the testing and confirmation of scientific hypotheses. Bayes or Bust? provides the first balanced treatment of the complex set of issues involved in this nagging conundrum in the philosophy of science. Both Bayesians and anti-Bayesians will find a wealth of new insights on topics ranging from Bayes's original paper to contemporary formal learning theory. In a paper published posthumously in 1763, the Reverend Thomas Bayes made a seminal contribution to the understanding of "analogical or inductive reasoning." Building on his insights, modem Bayesians have developed an account of scientific inference that has attracted numerous champions as well as numerous detractors. Earman argues that Bayesianism provides the best hope for a comprehensive and unified account of scientific inference, yet the presently available versions of Bayesianisin fail to do justice to several aspects of the testing and confirming of scientific theories and hypotheses. By focusing on the need for a resolution to this impasse, Earman sharpens the issues on which a resolution turns. John Earman is Professor of History and Philosophy of Science at the University of Pittsburgh.