Lectures
Lectures are on Tuesdays and Thursdays 2:30 - 3:50 pm in CIT 368.
Primary readings below refer to sections in the course textbook, Introduction to Probability (second edition) by Bertsekas and Tsitsiklis. For material in the first half of the course, Pitman's Probability is recommended as a secondary reference.
| # | Date | Topics | Primary Reading | Materials |
|---|---|---|---|---|
| 0 | 9/6 | Course Overview | n.a. | Slides | 1 | 9/12 | Sets and Counting | 1.1,1.6 | Slides |
| 2 | 9/14 | Probability, Conditioning, Bayes | 1.2-1.4 | Slides |
| 3 | 9/19 | Independence, Bayes | 1.2-1.4 | Slides |
| 4-5 | 9/21, 9/26 | Discrete RV, Expectation | 2.1-2.2 | Slides |
| 6-7 | 9/28, 10/03 | Joint RV's, Conditional Distributions | 2.4-2.7 | Slides |
| 8 | 10/05 | Markov inequality, Variance, Chebyshev's inequality | 2.4,5.1 | Slides |
| 9 | 10/10, 10/12 | Continuous R.V.'s, Gaussian | 3.1-3.3 | Slides |
| 10 | 10/17, 10/19 | Central Limit Theorem, Confidence Interval, Finite Sample Bounds | 3.4,4.2 | Slides |
| 11 | 10/26 | Marginal and Conditional Densities | 3.3-6 | Slides |
| 12 | 10/31 | Covariance,Bivaraite Normal Distributions | 4.2 | Slides |
| 13 | 11/2, 11/7 | Monte Carlo | 7.1 | Slides |
| 14 | 11/9 | Markov Chains, Multi-step Transition Distributions | 7.1-7.4 | Slides |
| 16 | 11/14, 11/16 | Markov Chains, Recurrence, Stationary Distribution | 7.4 | Slides |
| 19 | 11/21 - 11/28 | Statistics | Chapter 9 | Slides |
| 20 | 12/05 - 12/07 | Parameter Estimation, Maximum Likelihood | Chapter 8 | Slides |
| 21 | 12/07 | Review | Selected Topics | Slides |