Modern Regression Methods / Edition 2

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Regression is a common statistical technique. This synthesis of the state-of-the-art regression methodology features a data analysis orientation and comprehensive treatment of regression diagnostics.
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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 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 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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