Part 1 Single-Equation Regression Models 1. The Nature of Regression Analysis 2. Two-Variable Regression Analysis Some Basic Ideas 3. Two-Variable Regression Model The Problem of Estimation 4. The Normality Assumption Classical Normal Linear Regression Model (CNLRM) 5. Two-Variable Regression Interval Estimation and Hypothesis Testing 6. Extensions of the Two-Variable Linear Regression Model 7. Multiple Regression Analysis The Problem of Estimation 8. Multiple V Analysis The Problem of Inference 9. The Matrix Approach to Linear Regression Model Part 2 Relaxing the Assumptions of the Classical Model 10. Multicollinearity and Micronumerosity 11. Heteroscedasticity 12. Autocorrelation 13. Econometric Modeling I Traditional Econometric Methodology 14. Econometric Modeling II Alternative Econometric Methodology Part 3 Topics in Econometrics 15. Regression on Dummy Variables 16. Regression on Dummy Dependent Variable The LPM Logit Probit and Tobit Models 17. Dynamic Econometric Model Autoregressive and Distributed-Lag Models Part 4 Simulataneous-Equation Mpdels 18. Simultaneous-Equation Models 19. The Identification Problem 20. Simulataneous-Equation Methods Part 5 Time Series Econometrics 21. Time Series Econometric I Stationarity Unit Roots and Coiuntegration 22. Time Series Econometric II Forecasting with ARIMA and VAR Models