This book is an introduction to regression analysis for upper division and graduate students in science, engineering, social science and medicine. The emphasis is on the classical linear regression diagnostics, ridge and logistic regression are treated as well. In contrast to other books at this level, the theoretical foundation of the subject is presented in some detail based on extensive use of matrix algebra. throughout the text, model building and evaluation are emphasized and illustrated with many numerical examples.
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"can be a useful addition to academic libraries will find it helpful in further understanding the underlying theory and applications" "In my opinion this book can be a useful addition to academic libraries and readers with basic statistical knowledge will find it helpful in further understanding theory and application of the regression analysis." --E-STREAMS Online Journal, Vol 8, No 5 May 2005 --E-STREAMS Online Journal, Vol 8, No 5, May 2005
Highly recommended, more appropriate as a resource for a two-semester course, than a one-semester course. Upper division undergraduates through faculty and researchers" --CHOICE, February 2005
"Provides a level of mathematical detail not seen in other graduate student and advanced undergraduate regression texts." "those looking to acquire a solid regression reference...should certainly consider this book" --The American Statistician, Vol 61, No 1, February 2007
Highly recommended, more appropriate as a resource for a two-semester course, than a one-semester course. Upper division undergraduates through faculty and researchers" --CHOICE, February 2005
"Provides a level of mathematical detail not seen in other graduate student and advanced undergraduate regression texts." "those looking to acquire a solid regression reference...should certainly consider this book" --The American Statistician, Vol 61, No 1, February 2007
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