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Rating: 
Summary: Clear and thorough - a personal favorite
Review: I'm no statistician, but have to perform statistical analyses anyway. That's why I value a book like this. It's very approachable, given some linear algebra, a gives a great, practical review of linear regression. This book doesn't just give clear descriptions of regression and linear discriminators. It also shows how, and more importantly why, I should set control parameters. Best of all, it shows how to measure the quality of the results given by most techniques. Too many people just turn the crank on their algorithms blindly, never knowing what they've computed (if anything). I am very happy to see a text shows me how to determine whether its techniques are working well on any specific problem. On the whole, I find the presentation readable and practical. There's some theory, but just enough to give real understanding, and to give some ability to tune the techniques to the problem at hand. This book is one of my real workhorses - I recommed it highly.
Rating:
Summary: modern coverage of regression including Minitab macros
Review: Usually books on regression analysis deal with only linear regression. This text includes thorough coverage of the standard regression topics but also includes chapters on logistic regression, nonparametric regression, robust regression, ridge regression and nonlinear regression. Recent tools including the bootstrap are covered. Software for ridge regression is discussed and a Minitab macro is given in Appendix A. Software is also provided in the attached diskette with installation instructions in Appendix A. Ryan is an excellent writer who does not assume a high level of mathematical sophistication. He has also written an earlier text on statistical quality control "Statistical Methods for Quality Improvement" which came out in a second edition earlier this year.
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