Regression Analysis by Example / Edition 5

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Overview

A variety of ideas and methods of regression analysis are explored with the aid of realistic examples that highlight the analysis of data and include irregularities similar to those encountered in practice. Recent advances in regression diagnostics are covered with emphasis on plots such as component plus residual, added variable, sequence, along with index plots for leverage and function. The authors utilize standard and some not so standard summary statistics on the basis of their intuitive appeal to demonstrate concepts. The majority of analyses described are available in software packages on the market today.
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Editorial Reviews

Statistician
This book is a thorough overview and introduction to regression analysis that is sensibly arranged and easy to read. Care has been taken to provide verbal explanations for quantitative and algebraic expressions, and to provide interpretations for statistical results and insights.
SciTech Book News
A textbook for students who have some background in statistics but are not specialists in it, and who use regression analysis quite extensively in their work. Students who are specializing in statistics might find it a useful balance...
Technometrics
Overall, the material that is covered is an excellent introduction to a substantial collection of diagnostic tools that aid in uncovering hidden structures in one's data. I would recommend the book as an addition to any applied statistician's library.
Statistician
This book is a thorough overview and introduction to regression analysis that is sensibly arranged and easy to read. Care has been taken to provide verbal explanations for quantitative and algebraic expressions, and to provide interpretations for statistical results and insights.
Booknews
A textbook for students who have some background in statistics but are not specialists in it, and who use regression analysis quite extensively in their work. Students who are specializing in statistics might find it a useful balance to the abstract approach of most standard textbooks. Chatterjee (statistics, New York U.), Ali S. Hadi (statistical and computing sciences, Cornell U.) and consultant Bertram Price emphasize analyzing data rather than formulas, testing hypotheses, or confidence intervals, and therefore make no attempt to derive the techniques they describe. They mention no date for earlier editions, but have extensively rewritten the third edition and expanded it from nine chapters to twelve. Annotation c. Book News, Inc., Portland, OR (booknews.com)
From the Publisher
"This book is now well established as an excellent source of examples for regression analysis. It has been and still is readily readable and understandable to those with a minimum of data analytic experience.... It is an excellent source of information and example analyses concerning regression modeling for the beginning to moderately trained data analyst." (Journal of the American Statistical Association, March 2009)

"This book is now well established as an excellent source of examples for regression analysis.  It has been and still is readily readable and understandable to those with a minimum of data analytic experience … It is an excellent source of information and example analyses concerning regression modeling for the beginning to moderately trained data analyst." (Journal of the American Statistical Association, March 2009)

"I would like to have the new edition on my desk and suggest you do as well!" (Technometrics, May 2007)

"…I would recommend this book for all students…interested in regression modeling…" (MAA Reviews, December 12, 2006)

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Product Details

  • ISBN-13: 9780470905845
  • Publisher: Wiley, John & Sons, Incorporated
  • Publication date: 8/28/2012
  • Series: Wiley Series in Probability and Statistics Series , #866
  • Edition description: New Edition
  • Edition number: 5
  • Pages: 424
  • Sales rank: 920,097
  • Product dimensions: 9.90 (w) x 7.20 (h) x 1.20 (d)

Meet the Author

SAMPRIT CHATTERJEE, PHD, is Professor of Health Policy at Mount Sinai School of Medicine. He is also Professor Emeritus of Statistics at New York University. A well-known research scientist and Fulbright scholar, Dr. Chatterjee has co-authored Sensitivity Analysis in Linear Regression (with Dr. Hadi) and A Casebook for a First Course in Statistics and Data Analysis, both published by Wiley.

ALI S. HADI, PHD, is Vice Provost and Professor of Mathematical, Statistical, and Computing Sciences at The American University in Cairo. He is also a Stephen H. Weiss Presidential Fellow and Professor Emeritus at Cornell University. Dr. Hadi is the author/co-author of four other books, a Fellow of the American Statistical Association, and an elected member of the International Statistical Institute.

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Read an Excerpt

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Table of Contents

Simple Linear Regression.
Detection and Correction of Model Violations: Simple Linear Regression.
Multiple Regression Model.
Qualitative Variables as Regressors.
Weighted Least Squares.
The Problem of Correlated Errors.
Analysis of Collinear Data.
Biased Estimation of Regression Coefficients.
Selection of Variables in a Regression Equation.
Selected Problems.
Statistical Tables.
Index.
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