This reader-friendly book focuses on building linear statistical models and developing skills for implementing regression analysis in real-life situations. It includes applications for a range of fields including engineering, sociology, and psychology, as well as traditional business applications. The authors use the latest material available from news articles, magazines, professional journals, the Internet, and actual consulting problems to illustrate real business situations and how to solve them using the tools of regression analysis. In addition, this book emphasizes model building and multiple regression models and pays special attention to model validation and spline regression. For professionals in any number of fields, including engineering, sociology, and psychology, who would benefit from learning how to use regression analysis to solve problems.
Table of Contents
1. Review of Basic Concepts (Optional). 2. Introduction to Regression Analysis. 3. Simple Linear Regression. 4. Multiple Regression. 5. Model Building. 6. Some Regression Pitfalls. 7. Residual Analysis. 8. Special Topics in Regression (Optional). 9. Time Series Modeling and Forecasting. 10. Principles of Experimental Design. 11. The Analysis of Variance for Designed Experiments. (Note: the following chapters are case studies.) 12. Modeling the Sale Prices of Residential Properties in Four Neighborhoods. 13. An Analysis in Rain Levels in California. 14. Reluctance to Transmit Bad News: The MUM Effect. 15. An Investigation of Factors Affecting the Sale Price of Condominium Units Sold at Public Auction. 16. Modeling Daily Peak Electricity Demands. Appendix A: The Mechanics of a Multiple Regression Analysis. Appendix B: A Procedure for Inverting a Matrix. Appendix C: Useful Statistical Tables. Appendix D: SAS Tutorial. Appendix E: SPSS Tutorial. Appendix F: MINITAB Tutorial. Appendix G: ASP Tutorial Data Sets. Answers to Odd-Numbered Exercises. Index.