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Rating: 
Summary: Super Book
Review: I have used this book from first edition in the early 1980's in grad school to lastest edition in 2003. A very good book, designed to be used with statistical software. The authors understand the field and provide a thorough yet concise perspective of mainly regression and ANOVA models. An absolute must book for the applied statistician.
Rating:
Summary: Super Book
Review: I have used this book from first edition in the early 1980's in grad school to lastest edition in 2003. A very good book, designed to be used with statistical software. The authors understand the field and provide a thorough yet concise perspective of mainly regression and ANOVA models. An absolute must book for the applied statistician.
Rating:
Summary: Excellent Introduction to Linear Regression
Review: I used this book for a second level statistics course for my Master's degree in Epidemiology. I liked it!All the underlying math you want to know is sitting on the pages, clearly explained though examples with computer output and graphs. I worked through the problems in the text without difficulty and reproduced their work. I understood what I was doing. Each chapter is followed by a series of problems. You probably want to get a solutions manual if you want to check your answers. The material covered includes: Univariable and multivariable linear regression, correlations including multiple partial, ANOVA, ANCOVA, Polynomial Regression including orthogonal polynomials, dummy variables, selecting best regression equation, and introductions to repeated measures ANOVA, maximum likelihood methods, and logistic regression. Now that I feel that I have these basics under control, I would like a book on "approaches" to data and dealing with "difficult" data. This book contains one chapter on regression diagnostics -- not enough. But I guess that is the next step.... Other readers have commented on other books addressing the same topic, unfortunately I have not read those other books. However, I am certain that you will learn from this book, and when you are done, you will be ready for more. (Did I mention that I signed up for a course with Dr. Kleinbaum on analysis of matched data?)
Rating: 
Summary: Not that great
Review: I was surprised when I took this class that I did not like this book. All of my epid profs highly recommended this text. You have to flip back and forth when you are doing the problems because they list the SAS output that you need once in one chapter. I know it saves space, but this can get maddening. I did not find the examples clearly written at all-the lack of fit test, and some of the stuff about partial F tests could have used a few more sentences.
No, I cannot write a glowing review of the text, but the only reason for the second star is because I also had a terrible instructor for this course. Perhaps if Dr. Kleinbaum had taught this to me, I would have a different perspective of this book. However, I was pretty much teaching myself this material, and this book is not designed for that.
Rating: 
Summary: Not my favorite
Review: The most complete and cristal clear exposition of multivariate analisys I ever read.
Rating:
Summary: Top of the line for multivariate issues understanding
Review: The most complete and cristal clear exposition of multivariate analisys I ever read.
Rating:
Summary: Not my favorite
Review: This book skips some important basic concepts and has several poor, glossed-over explantions. I'd recommend Neter or Mendenhall.
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