All readings refer to 
DeGroot, Morris H., and Mark J. Schervish. Probability and Statistics. 3rd ed. Boston, MA: Addison-Wesley, 2002. ISBN: 0201524880.
| SES # | TOPICS | READINGS |
|---|---|---|
| L1 | Overview of some Probability Distributions | |
| L2 | Maximum Likelihood Estimators | Section 6.5 |
| L3 | Properties of Maximum Likelihood Estimators | Sections 6.6 and 7.8 |
| L4 | Multivariate Normal Distribution and CLT | Section 5.12 (for the 2-dimensional case) |
| L5 | Confidence Intervals for Parameters of Normal Distribution | Sections 7.3 and 7.5 |
| L6 | Gamma, Chi-squared, Student T and Fisher F Distributions | Sections 5.9, 7.2, 7.4, and 8.7 |
| L7-L8 | Testing Hypotheses about Parameters of Normal Distribution, t-Tests and F-Tests | Sections 8.5, 8.6, and 8.7 |
| L9 |
Testing Simple Hypotheses Bayes Decision Rules |
Sections 8.1-8.2 |
| L10 | Most Powerful Test for Two Simple Hypotheses | Section 8.2 |
| L11 | Chi-squared Goodness-of-fit Test | Section 9.1 |
| L12 | Chi-squared Goodness-of-fit Test for Composite Hypotheses | Section 9.2 |
| L13 | Tests of Independence and Homogeneity | Sections 9.3, 9.4, and 9.5 |
| L14 | Kolmogorov-Smirnov Test | Section 9.6 |
| L15-L16 | Simple Linear Regression | Sections 10.1, 10.2, and 10.3 |
| L17-L18 | Multiple Linear Regression | Section 10.5 |
| L19-L20 |
General Linear Constraints in Multiple Linear Regression Analysis of Variance and Covariance |
Sections 10.6, 10.7, and 10.8 |
| L21 | Classification Problem, AdaBoost Algorithm | |
| L22 | Review |