A comprehensive and current introduction to the fundamentals of regression analysisIntroduction to Linear Regression Analysis, 6th Edition is the most comprehensive, fulsome, and current examination of the foundations of linear regression analysis. Fully updated in this new sixth edition, the distinguished authors have included new material on generalized regression techniques and new examples to help the reader understand retain the concepts taught in the book.The new edition focuses on four key areas of improvement over the fifth edition:* New exercises and data sets* New material on generalized regression techniques* The inclusion of JMP software in key areas* Carefully condensing the text where possibleIntroduction to Linear Regression Analysis skillfully blends theory and application in both the conventional and less common uses of regression analysis in today's cutting-edge scientific research. The text equips readers to understand the basic principles needed to apply regression model-building techniques in various fields of study, including engineering, management, and the health sciences.

Preface vii2 Simple Linear Regression 13 Multiple Linear Regression 134 Model Adequacy Checking 295 Transformations and Weighting to Correct Model Inadequacies 596 Diagnostics for Leverage and Influence 747 Polynomial Regression Models 798 Indicator Variables 869 Multicollinearity 9510 Variable Selection and Model Building 10011 Validation of Regression Models 10512 Introduction to Nonlinear Regression 10813 Generalized Linear Models 11314 Regression Analysis of Time Series Data 12115 Other Topics in the Use of Regression Analysis 125