Regression Analysis by Example (Wiley Series in Probability and Statistics – Applied Probability and Statistics Section) - Hardcover

Chatterjee, Samprit; Price, Bertram

3.61

44 ratings by Goodreads

9780471015215: Regression Analysis by Example (Wiley Series in Probability and Statistics – Applied Probability and Statistics Section)

Hardcover

ISBN 10: 0471015210 ISBN 13: 9780471015215

Publisher: Wiley–Blackwell, 1977

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Bridges the gap between theory and practice of regression analysis, providing a balance between theoretical results, empirical rules, and the analyst's subjective judgment. Describes methods by using realistic examples that emphasize the analysis of data and that contain irregularities similar to those encountered in practice. Demonstrates concepts by utilizing standard--and some not so standard--summary statistics on the basis of their intuitive appeal.

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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)

"...for students who have some background in statistics but are not specialists in it, and who use regression analysis quite extensively..." ( SciTech Book News, Vol. 24, No. 4, December 2000)

...excellent introduction to a substantial collection of diagnostic tools that aid in uncovering hidden structures in one′s data. (Technometrics, Vol. 42, No. 4, May 2001)

[...] a thorough overview and introduction to regression analysis that is sensibly arranged and easy to read. (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 Back Cover:

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.

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