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Regression analysis is a vitally important statistical tool, with major advancements made by both practical data analysts and statistical theorists. In CLASSICAL AND MODERN REGRESSION WITH APPLICATIONS, Second Edition, Raymond H. Myers provides a solid foundation in classical regression, while introducing modern techniques. Throughout the text, a broad spectrum of applications are included from the physical sciences, engineering, biology, management, and economics.
1. Introduction: Regression Analysis 2. The Simple Linear Regression Model 3. The Multiple Linear Regression Model 4. Criteria for Choice of Best Model 5. Analysis of Residuals 6. Influence Diagnostics 7. Nonstandard Conditions, Violations of Assumptions, and Transformations 8. Detecting and Combating Multicollinearity 9. Nonlinear Regression Appendix A: Some Special Concepts in Matrix Algebra / Appendix B: Some Special Manipulations / Appendix C: Statistical Tables
Overview
Regression analysis is a vitally important statistical tool, with major advancements made by both practical data analysts and statistical theorists. In CLASSICAL AND MODERN REGRESSION WITH APPLICATIONS, Second Edition, Raymond H. Myers provides a solid foundation in classical regression, while introducing modern techniques. Throughout the text, a broad spectrum of applications are included from the physical sciences, engineering, biology, management, and economics.