Regression Analysis by Example, 3rd Edition [Hardcover]

Samprit Chatterjee (Author), Ali S. Hadi (Author), Bertram Price (Author)

Book Description

Publication Date: November 15, 1999 | ISBN-10: 0471319465 | ISBN-13: 978-0471319467 | Edition: 3

Regression analysis provides a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgement. Regression Analysis by Example, Third Edition explains the principles underlying exploratory data analysis, emphasizing data analysis rather than statistical theory. This is not just another edition of the book; it is a major rewriting and reorganization of the previous edition. The new edition is expanded and updated to reflect recent advances in the field, offering in-depth treatment of diagnostic plots, time series regression, multicollinearity, and logistic regression.

Suitable for anyone with an understanding of elementary statistics, Regression Analysis by Example, Third Edition illustrates methods of regression analysis, with examples containing the types of irregularities commonly encountered in the real world. Each example isolates one or two techniques and features detailed discussions of the techniques themselves, the required assumptions, and the evaluated success of each technique. Each of the methods described can be carried out with most currently available statistical software packages.

Editorial Reviews

Review

"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..." (SciTech Book News, Vol. 24, No. 4, December 2000)

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. (Technometrics, Vol. 42, No. 4, May 2001)

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 quanitative and algebraic expressions, and to provide interpretations for statistical results and insights. (The Statistician, 50 (1), 2001)

"This book is a major rewriting and reorganization of previous editions. New material is added to reflect advances in the field." (Zentralblatt MATH, Vol. 946, No. 21)

"...a thorough overview of diagnostic tools for regression models that are sensibly arranged and easily understood..."(Statistical Methods in Medical Research, Vol.12, No.1, 2003)

From the Publisher

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. --This text refers to an out of print or unavailable edition of this title.

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Product Details

• Hardcover: 368 pages
• Publisher: Wiley-Interscience; 3 edition (November 15, 1999)
• Language: English
• ISBN-10: 0471319465
• ISBN-13: 978-0471319467
• Product Dimensions: 9.6 x 6.5 x 1 inches
• Shipping Weight: 1.5 pounds
• Average Customer Review: 3.8 out of 5 stars  See all reviews (6 customer reviews)
• Amazon Best Sellers Rank: #1,275,671 in Books (See Top 100 in Books)

Customer Reviews

Most Helpful Customer Reviews

6 of 6 people found the following review helpful:

5.0 out of 5 stars Great examples!, August 30, 2008

By 

Dragomir Voicu Dan "Asst. prof." (Bucharest, Romania) - See all my reviews

This review is from: Regression Analysis by Example (Wiley Series in Probability and Statistics) (Hardcover)

Its strength is in the examples. It is true that the book also employs formulas, but most of them are informative and fairly easy to follow if you have a moderate background in statistics. I would recommend this book for an intermediate course in econometrics, mainly because it offers a comprehensive view of the subject and ways to apply analysis tools. I give it five stars for the presence of applied data.

5 of 5 people found the following review helpful:

5.0 out of 5 stars Excellent Book, June 10, 2010

By 

Abhijeet Deshpande (USA) - See all my reviews
(REAL NAME)   

Amazon Verified Purchase

This review is from: Regression Analysis by Example, 3rd Edition (Hardcover)

Over the years, I have read many books on regression analysis. This book is one of the most lucidly written book on the subject. It achieves a fine balance between theoretical explanation and application of the method to real world problems. It requires some background knowledge, i.e. first college course of statistics, but it is not too dense. I am using this as a companion to a book on regression analysis by Douglas Montgomery (another excellent text). The best part is that the data and computer programs in SAS, R etc. are available on the UCLA website. All in all, a great resource.

17 of 22 people found the following review helpful:

3.0 out of 5 stars Thorough, but difficult to follow., April 10, 2006

By 

A Graduate Student (USA) - See all my reviews

This review is from: Regression Analysis by Example, 3rd Edition (Hardcover)

I used this book for an introductory/intermediate course in regression.

Although the authors presented a lot of material and I did find it informative, I found myself having to refer to other texts for a better explanation of about half of the material presented.

To me it read like an academic paper. It seemed that all the variables were explained only once in the text and used throughout the book without a central glossary or formula page. There also seemed to be a lot of subscripts and superscripts to the variables, as well as bouncing back and forth between data examples, which made following the concepts difficult.

There was a lot of information packed in the book's pages, but it was real difficult reading and trying to comprehend past the second chapter.