1. Statistical Tables
2. Raw Scores, Deviation Scores & Standard Scores
3. About Summation Signs
4. Variance, Covariance & Correlation
5. Linear Regression: An Intuitive Explanation
6. Simple Linear Regression
7. Regression Without Predictors
8. Regression Assumptions
9. Predicted Scores, Residuals and Other Goodies
10. Simple Linear Regression Session
11. A Derivation
12. Prediction Practice: Part 1
13. Multiple Linear Regression
14. "Four Regressions" in Concert
15. Prediction Practice: Part 2
16. Data Transformation
17. Regression Diagnostics
18. Index Plots
19. Dichotomous Predictors
20. Product Variables and Interactions
21. Multiple Regression Session
22. Collinearity
23. Selection and Prediction
24. Problems with Stepwise Regression
25. Cross Validation
26. Polynomial Regression
27. Partial and Semipartial Correlation
28. Comparing Regression Models
29. b vs β
30. Categorical Predictors
31. Prediction Practice: Part 3
32. Ordinal Predictor Variables
33. Interactions with Categorical Predictors
34. Centering
35. Some Scaling Issues
36. Analysis of Covariance
37. Aptitude Treatment Interaction
38. Logistic Regression
39. Robust Regression
40. Path Analysis
41. Linear Structural Models
42. Specification Error
43. Regression with Clustered Data
44. Multilevel Data Issues
45. Regression with Measurement Error
46. Nonlinear Regression
47. Weighted Least Squares
48. Regression Analysis in Publications
49. The Regression Zoo
50. The Matrix
51. Generalized Linear Models

Linear Statistical Models Course