Details

Regression Analysis by Example

Wiley Series in Probability and Statistics, Band 607 4. Aufl.

von: Samprit Chatterjee, Ali S. Hadi
103,99 €
Verlag:	Wiley
Format:	PDF
Veröffentl.:	20.10.2006
ISBN/EAN:	9780470055458
Sprache:	englisch
Anzahl Seiten:	416

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Beschreibungen

Titelbeschreibung

The essentials of regression analysis through practical applications Regression analysis is 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, Fourth Edition has been expanded and thoroughly updated to reflect recent advances in the field. The emphasis continues to be on exploratory data analysis rather than statistical theory. The book offers in-depth treatment of regression diagnostics, transformation, multicollinearity, logistic regression, and robust regression. This new edition features the following enhancements: <ul class="noindent"> <li>Chapter 12, Logistic Regression, is expanded to reflect the increased use of the logit models in statistical analysis </li> <li>A new chapter entitled Further Topics discusses advanced areas of regression analysis </li> <li>Reorganized, expanded, and upgraded exercises appear at the end of each chapter </li> <li>A fully integrated Web page provides data sets </li> <li>Numerous graphical displays highlight the significance of visual appeal Regression Analysis by Example, Fourth Edition is suitable for anyone with an understanding of elementary statistics. Methods of regression analysis are clearly demonstrated, and examples containing the types of irregularities commonly encountered in the real world are provided. 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. The methods described throughout the book can be carried out with most of the currently available statistical software packages, such as the software package R. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.</li> </ul>

Inhaltsverzeichnis

Preface. 1. Introduction. 2. Simple Linear regression. 3. Multiple Linear Regression. 4. Regression Diagnostics: Detection of Model Violations. 5. Qualitative Variables as Predictors. 6. Transformation of Variables. 7. Weighted Least Squar45es. 8. The Problem of Correlated Errors. 9. Analysis of Collinear Data. 10. Biased Estimation of Regression Coefficients. 11. Variable Selection Procedures. 12. Logistic Regression. 13. Further Topics. Appendix A: Statistical Tables. References. Index.

Rezension

"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)

Autorenportrait

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.

Back cover copy

The essentials of regression analysis through practical applications Regression analysis is 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, Fourth Edition has been expanded and thoroughly updated to reflect recent advances in the field. The emphasis continues to be on exploratory data analysis rather than statistical theory. The book offers in-depth treatment of regression diagnostics, transformation, multicollinearity, logistic regression, and robust regression. This new edition features the following enhancements: <ul> <li>Chapter 12, Logistic Regression, is expanded to reflect the increased use of the logit models in statistical analysis</li> <li>A new chapter entitled Further Topics discusses advanced areas of regression analysis</li> <li>Reorganized, expanded, and upgraded exercises appear at the end of each chapter</li> <li>A fully integrated Web page provides data sets</li> <li>Numerous graphical displays highlight the significance of visual appeal</li> </ul> Regression Analysis by Example, Fourth Edition is suitable for anyone with an understanding of elementary statistics. Methods of regression analysis are clearly demonstrated, and examples containing the types of irregularities commonly encountered in the real world are provided. 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. The methods described throughout the book can be carried out with most of the currently available statistical software packages, such as the software package R.