Part I: Single-Equation Regression Model§ Chapter 1: The Nature of Regression Analysis§ Chapter 2: Two-Variable Regression Analysis: Some Basic Ideas§ Chapter 3: Two Variable Regression Model: The Problem of Estimation§ Chapter 4: Classical Normal Linear Regression Model (CNLRM)§ Chapter 5: Two-Variable Regression: Interval Estimation and Hypothesis Testing§ Chapter 6: Extensions of the Two-Variable Linear Regression Model§ Chapter 7: Multiple Regression Analysis: The Problem of Estimation§ Chapter 8: Multiple Regression Analysis: The Problem of Inference§ Chapter 9: Dummy Variable Regression Models§Part II: Relaxing the Assumptions of the Classical Model§ Chapter 10: Multicollinearity: What happens if the Regressor are Correlated§ Chapter 11: Heteroscedasticity: What Happens if the Error Variance is Nonconstant?§ Chapter 12: Autocorrelation: What Happens if the Error Terms are Correlated§ Chapter 13: Econometric Modeling: Model Specification and Diagnostic Testing§Part III: Topics in Econometrics§ Chapter 14: Nonlinear Regression Models§ Chapter 15: Qualitative Response Regression Models§ Chapter 16: Panel Data Regression Models§ Chapter 17: Dynamic Econometric Model: Autoregressive and Distributed-Lag Models.§Part IV: Simultaneous-Equation Models§ Chapter 18: Simultaneous-Equation Models.§ Chapter 19: The Identification Problem.§ Chapter 20: Simultaneous-Equation Methods.§ Chapter 21: Time Series Econometrics: Some Basic Concepts§ Chapter 22: Time Series Econometrics: Forecasting§ Appendix A: Review of Some Statistical Concepts§ Appendix B: Rudiments of Matrix Algebra§ Appendix C: The Matrix Approach to Linear Regression Model§ Appendix D: Statistical Tables§ Appendix E: Computer Output of EViews, MINITAB, Excel, and STATA§ Appendix F: Economic Data on the World Wide Web§ leírás elrejtése