Modern Regression Methods / Edition 2

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Overview

"Over the years, I have had the opportunity to teach several regression courses, and I cannot think of a better undergraduate text than this one." (The American Statistician)

"The book is well written and has many exercises. It can serve as a very good textbook for scientists and engineers, with only basic statistics as a prerequisite. I also highly recommend it to practitioners who want to solve real-life prediction problems." (Computing Reviews)

Modern Regression Methods, Second Edition maintains the accessible organization, breadth of coverage, and cutting-edge appeal that earned its predecessor the title of being one of the top five books for statisticians by an Amstat News book editor in 2003. This new edition has been updated and enhanced to include all-new information on the latest advances and research in the evolving field of regression analysis.

The book provides a unique treatment of fundamental regression methods, such as diagnostics, transformations, robust regression, and ridge regression. Unifying key concepts and procedures, this new edition emphasizes applications to provide a more hands-on and comprehensive understanding of regression diagnostics. New features of the Second Edition include:

  • A revised chapter on logistic regression, including improved methods of parameter estimation
  • A new chapter focusing on additional topics of study in regression, including quantile regression, semiparametric regression, and Poisson regression
  • A wealth of new and updated exercises with worked solutions
  • An extensive FTP site complete with Minitab macros, which allow the reader to compute analyses, and specialized procedures
  • Updated references at the end of each chapter that direct the reader to the appropriate resources for further study

An accessible guide to state-of-the-art regression techniques, Modern Regression Methods, Second Edition is an excellent book for courses in regression analysis at the upper-undergraduate and graduate levels. It is also a valuable reference for practicing statisticians, engineers, and physical scientists.

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Editorial Reviews

From the Publisher
"The book is to be praised in that it makes the reader aware of a large number of approaches to regression situations, and also to their possible pitfalls. It is thus an excellent basis for an experienced instructor to teach regression at different levels." (Springer, August 2010)

"This book, at the undergraduate level and even at the graduate level, will be rewarding reading for anyone interested in learning the nuances of regression analysis." (Mathmatical Reviews, January 2010)

"The exercises are interesting and thought-provoking throughout. If you liked the first edition, you will be pleased with this revision also." (International Statistical Review, August 2009)

"The book is well written and has many exercises. It can serve as a very good textbook for scientists and engineers, with only basic statistics as a prerequisite. I also highly recommend it to practitioners who want to solve real-life prediction problems." (Computing Reviews, July 2009)

"In this second edition, Ryan (author, editor, and educator) provides substantial updates and revisions of his popular text for statisticians to include new information on the most current advances and research in regression analysis" (SciTech Reviews, March 2009)

"One would be hard-pressed to find another text that rivals this one in terms of coverage of the regression literature." (The American Statistician, 2009)

"I strongly recommend the book as a reference for anyone teaching or using regression." (MAA Reviews, 2009)

"Highly recommended for those already trained in mathematics and statistics who want a good guide to current practice and issues in multiple regression techniques." (Journal of Biopharmaceutical Statistics, 2009)

Australian & New Zealand Statistics
...an excellent book...worthwhile for anyone that uses regression techniques to obtain their own copy of this book...
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Product Details

  • ISBN-13: 9780470096062
  • Publisher: Wiley
  • Publication date: 1/9/2009
  • Edition description: Solution M
  • Edition number: 2
  • Pages: 128
  • Product dimensions: 6.22 (w) x 9.27 (h) x 0.36 (d)

Meet the Author

Thomas P. Ryan, PhD, served on the Editorial Review Board of the Journal of Quality Technology from 1990–2006, including three years as the book review editor. He is the author of four books, all of which are published by Wiley, and he is also an elected Fellow of the American Statistical Association, the American Society for Quality, and the Royal Statistical Society. A former consultant to Cytel Software Corporation, Dr. Ryan currently teaches advanced courses at statistics.com on the design of experiments, statistical process control, and engineering statistics.

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Table of Contents

1 Introduction 1
2 Diagnostics and Remedial Measures 44
3 Regression with Matrix Algebra 101
4 Introduction to Multiple Linear Regression 118
5 Plots in Multiple Regression 144
6 Transformations in Multiple Regression 183
7 Selection of Regressors 220
8 Polynomial and Trigonometric Terms 240
9 Logistic Regression 255
10 Nonparametric Regression 314
11 Robust Regression 348
12 Ridge Regression 396
13 Nonlinear Regression 416
14 Experimental Designs for Regression 446
15 Applications of Regression 468
Appendix A List of Minitab Macros 498
Appendix B Statistical Tables 501
Appendix C Answers to Selected Exercises 506
Index 511
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