To make econometrics relevant in an introductory course, interesting applications must motivate the theory and the theory must match the applications. This text aims to motivate the need for tools with concrete applications, providing simple assumptions that match the application.

I. INTRODUCTION AND REVIEW. 1. Economic Questions and Data. 2. Review of Probability. 3. Review of Statistics. II. FUNDAMENTALS OF REGRESSION ANALYSIS. 4. Linear Regression with One Regressor. 5. Linear Regression with Multiple Regressors. 6. Nonlinear Regression Functions. 7. Assessing Studies Based on Multiple Regression. III. FURTHER TOPICS IN REGRESSION ANALYSIS. 8. Regression with Panel Data. 9. Regression with a Binary Dependent Variable. 10. Instrumental Variables Regression. 11. Experiments and Quasi Experiments. IV. REGRESSION ANALYSIS OF ECONOMIC TIME SERIES DATA. 12. Introduction to Time Series Regression and Forecasting. 13. Estimation of Dynamic Causal Effects. 14. Additional Topics in Time Series Regression. V. THE ECONOMETRIC THEORY OF REGRESSION ANALYSIS. 15. The Theory of Linear Regression with One Regressor. 16. The Theory of Multiple Regression. Appendix: Statistical Tables.