Notes

1. Introduction
2. Probability Distributions
3. More probability
4. Asymptotics
5. Regression 1
   
6. Digression on probability functions in Stata and gretl. gretl script for computing probabilities.
   
7. Notes on least squares
8. Estimator Properties (9/18)
9. Sampling variation, Monte Carlo, Nonlinear models (9/20)
   
• GRETL: Nonlinear
• GRETL: Monte Carlo
10. Hypothesis tests in general
11. Confidence Intervals
12. Regression with binary variables
13. Linear Combination of parameters and forecast variance (10/4) and the gretl code.
    
14. Output and rescaling
15. Functional Forms
    
16. log-linear model and growth (10/16)
17. Multiple Regression
18. Polynomials and Interactions (10/25)
19. Multiple Hypotheses
    
• GRETL: mlb.inp
• mlb.gdt
20. Joint tests vs individual t-tests
21. Restricted Least Squares
22. More model specification issues
23. Indicator Variables
24. Experiments and Quasi-experiments
25. Heteroskedasticity