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Table of Contents
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
Answers to Odd-Numbered Exercises.