1. Introducing SAS 1 2. The Simple Linear Regression Model 50 3. Interval Estimation and Hypothesis Testing 82 4. Prediction, Goodness-of-Fit, and Modeling Issues 103 5. The Multiple Regression Model 130 6. Further Inference in the Multiple Regression Model 162 7. Using Indicator Variables 190 8. Heteroskedasticity 207 9. Regression with Time-Series Data: Stationary Variables 264 10. Random Regressors and Moment-Based Estimation 304 11. Simultaneous Equations Models 346 12. Regression with Time-Series Data: Nonstationary Variables 369 13. Vector Error Correction and Vector Autoregressive Models 390 14. Time-Varying Volatility and ARCH Models 406 15. Panel Data Models 428 16. Qualitative and Limited Dependent Variable Models 468 Appendix A. Math Functions 522 Appendix B. Probability 528 Appendix C. Review of Statistical Inference 541