The Foundations of Statistics (Dover Books on Mathematics)

Book Details

• Author: Leonard J. Savage

• Publisher: Dover Publications

• Language: English

• Edition: New

• ISBN: 9780486623498

• Pages: 310

• Cover: Paperback, Illustrated

• Dimensions: 8.5 x 5.5 x 0.9 inches

About the Book

"Foundations of Statistics" by Leonard J. Savage is a landmark work in the field of statistics that brought forward a radical new approach to probability theory. First published in 1954, Savage’s work revolutionized statistical thought by introducing the personalistic interpretation of probability, a concept that challenges the then-dominant frequentist approach. This book is widely considered one of the most important contributions to modern statistical philosophy.

The first seven chapters of the book lay out the theoretical foundations of Savage’s personal probability, addressing crucial concepts such as decision making under uncertainty, the sure-thing principle, qualitative and quantitative personal probabilities, and the role of utility in decisions. Savage explores these concepts in depth, drawing on both theoretical and practical aspects of probability.

In the latter part of the book, chapters eight through seventeen, Savage shifts focus to the practical application of statistics from the personalistic viewpoint. He delves into topics like minimax problems, estimation, testing theories, and other key statistical devices, offering a fresh perspective on how probability and statistics interact in decision-making processes.

What makes this edition even more valuable is the new preface, footnotes, and a comprehensive annotated bibliography that Leonard J. Savage included, providing insights into the evolution of his thoughts and reflections over the years. These additions mark this edition as Savage’s final analysis on the controversy of statistical foundations.

For students, researchers, and anyone interested in the philosophical underpinnings of statistics, "Foundations of Statistics" is a must-read that continues to inspire and provoke discussion in the world of statistical theory.