Applied Linear Regression Models continues to provide a thoughtful and understandable blend of the theory and applications of regression models in real life situations. In this Fourth Edition, the authors have provided improved organization and expanded coverage of key concepts such as model selection and validation, logistic regression, regression trees, and neural networks. The use of graphics and real-world data sets in examples, exercises, and case studies has been intensified, reflecting the ever-increasing role of computing in statistics and modeling. Hundreds of professors and other researchers have provided valuable suggestions and contributed directly or indirectly to the final contents of this text as well as the related Applied Linear Statistics Models, Fifth Edition-forthcoming. The author team and the McGraw-Hill Company are grateful to all. Book jacket.