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:
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
"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)
"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)
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.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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