Key Dates:
A more detailed schedule is available below. Please check this site regularly as the sequence of topics may have to be slightly modified.
Note:
Week | Date | Topic |
1 | Tu 01/09 | Review of the course syllabus. Introduction and basic concepts. Sections 1.1-1.4. |
Th 01/11 | Definition of probability and finite sample spaces. Sections 1.5-1.6. | |
2 | Tu 01/16 | Counting methods. Combinatorial methods. Multinomial coefficients. Sections 1.7-1.9. |
Th 01/18 | Union of events. Conditional probability and independent events. Sections 1.10 and 2.1-2.2. | |
3 | Tu 01/23 | Bayes' Theorem. Section 2.3. |
Th 01/25 |
Discrete random variables. Examples of discrete random variables. Sections 2.3, 3.1, 5.1-5.5. Quiz #1. |
|
4 | Tu 01/30 | Examples of discrete random variables. Continuous random variables. The CDF. Sections 5.1-5.5, and 3.2-3.3. |
Th 02/01 | Bivariate distributions and marginal distributions. Sections 3.4 and 3.5. | |
5 | Tu 02/06 | Conditional distributions. Section 3.6 |
Th 02/08 | Review | |
6 | Tu 02/13 | Midterm |
Th 02/15 | Multivariate distributions. Section 3.7. | |
7 | Tu 02/20 | Functions of random variables. Sections 3.8-3.9. |
Th 02/22 | Markov chains. Section 3.10 | |
8 | Tu 02/27 | Expectation and variances. Section 4.1-4.3 and 5.1-5.5. |
Th 03/01 |
Covariance and conditional expectation. Sections 4.6-4.7. Quiz #2. |
|
9 | Tu 03/06 | Covariance and conditional expectation. The normal distribution. Markov and Chebyshev's inequalities. Sections 4.6-4.7. Section 5.6. |
Th 03/08 | The law of large numbers and the central limit theorem. Sections 6.1-6.3 | |
10 | Tu 03/13 | More CLT examples. Other distributions: the gamma and beta distributions. The Poisson process. |
Th 03/15 |
Review. Quiz #3 (optional) |
|
Mon 03/19 | FINAL EXAM 9am-11am |