Principles of Statistical Inference

by D. R. Cox

Overview

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.

Product Details

ISBN-13:	9781139931380
Publisher:	Cambridge University Press
Publication date:	08/10/2006
Sold by:	Barnes & Noble
Format:	eBook
File size:	4 MB

About the Author

D. R. Cox is one of the world's preeminent statisticians. Author or co-author of sixteen books and roughly 250 papers, his work on the proportional hazards regression model is one of the most-cited and most influential papers in modern statistics.

Table of Contents

Preface; 1. Preliminaries; 2. Some concepts and simple applications; 3. Significance tests; 4. More complicated situations; 5. Some interpretational issues; 6. Asymptotic theory; 7. Further aspects of maximum likelihood; 8. Additional objectives; 9. Randomization-based analysis; Appendix A. A brief history; Appendix B. A personal view; References; Author index; Index.

Editorial Reviews

"A deep and beautifully elegant overview of statistical inference, from one of the towering figures who created modern statistics. This book should be essential reading for all who call themselves 'statistician'."
David Hand, Imperial College London

"On one level, it is a very useful and interesting introduction to statistical theory. On another level, it is a welcome personal statement by one of the foremost contributors to the foundations of inference."
M.E. Thompson, University of Waterloo, ISI Short Book Reviews

"The explanations of key concepts are written so clearly... that they may be understood even if the mathematical details are skipped. Hence, Principles of Statistical Inference may serve as a resource even for those without the
Sarah Boslaugh, MAA Online Read This!

"Cox’s Principles aims to describe and discuss fundamental tenets of statistical inference without deriving or proving anything. The result, a no-math tour through all of the major results, clearly achieves this aim and does so without “dumbing down” the subject in the least. On the contrary, the arguments leading up to important results and the discussions of the role of these results in statistical theory and practice are thorough and sophisticated. There are equations, used when equations are naturally needed to explain something. There just aren’t any proofs. The point is not to show the reader how to do mathematical statistics, but rather to explain to the reader what principles are involved in the process and why they are important. The focus is on the thinking rather than the mathematics. By eschewing the purely mathematical results, Cox is able to bring depth and perspective to a variety of implications, special cases, and counter-examples.
Biometrics

"This is a great book by a great statistician. Buy it and read it."
Ronald Christensen, Journal of the American Statistical Association

From the Publisher