A History Of Parametric Statistical Inference From Bernoulli To Fisher 1713 1935
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A History of Parametric Statistical Inference from Bernoulli to Fisher, 1713-1935
Author: Anders Hald
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-08-24
This is a history of parametric statistical inference, written by one of the most important historians of statistics of the 20th century, Anders Hald. This book can be viewed as a follow-up to his two most recent books, although this current text is much more streamlined and contains new analysis of many ideas and developments. And unlike his other books, which were encyclopedic by nature, this book can be used for a course on the topic, the only prerequisites being a basic course in probability and statistics. The book is divided into five main sections: * 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; * The Fisherian Revolution, 1912-1935. Throughout each of the chapters, the author provides lively biographical sketches of many of the main characters, including Laplace, Gauss, Edgeworth, Fisher, and Karl Pearson. He also examines the roles played by DeMoivre, James Bernoulli, and Lagrange, and he provides an accessible exposition of the work of R.A. Fisher. This book will be of interest to statisticians, mathematicians, undergraduate and graduate students, and historians of science.
Principles of Statistical Inference
Author: D. R. Cox
language: en
Publisher: Cambridge University Press
Release Date: 2006-08-10
In this definitive book, D. R. Cox gives a comprehensive and balanced appraisal of statistical inference. He develops the key concepts, describing and comparing the main ideas and controversies over foundational issues that have been keenly argued for more than two-hundred years. Continuing a sixty-year career of major contributions to statistical thought, no one is better placed to give this much-needed account of the field. An appendix gives a more personal assessment of the merits of different ideas. The content ranges from the traditional to the contemporary. While specific applications are not treated, the book is strongly motivated by applications across the sciences and associated technologies. The mathematics is kept as elementary as feasible, though previous knowledge of statistics is assumed. The book will be valued by every user or student of statistics who is serious about understanding the uncertainty inherent in conclusions from statistical analyses.
Probability Theory and Statistical Inference
Author: Aris Spanos
language: en
Publisher: Cambridge University Press
Release Date: 2019-09-19
This empirical research methods course enables informed implementation of statistical procedures, giving rise to trustworthy evidence.