All readings refer to DeGroot, Morris H., and Mark J. Schervish. Probability and Statistics. 3rd ed. Boston, MA: Addison-Wesley, 2002. ISBN: 0201524880.
Course readings.
| 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 |
|