| Date | Description |
|---|---|
| September 30 |
Overview Reading: BT 1.1, 1.2, 1.6, Intro to Schnapsen, Rules of Schnapsen |
| October 2 |
Counting: product rule, permutations Reading: Safety First (Schnapsen analysis) Trick mechanics |
| October 5 | Counting: combinations |
| October 7 | Counting: complementing, inclusion-exclusion, pigeonhole principle |
| October 9 | Intro to probability; equiprobable outcomes |
| October 12 |
Conditional probability Reading: BT 1.3, 1.5 |
| October 14 |
Law of Total Probability; Bayes' Theorem Reading: BT 1.4 |
| October 16 |
Independent events Reading: BT 2.1-2.3 |
| October 19 |
More independence Reading: BT 2.4 |
| October 21 |
Random variables, expectation Reading: Expected Game Points, last year's exercise |
| October 23 |
Linearity of expectation Reading: BT 2.7 |
| October 26 | Variance |
| October 28 | Independence; uniform distribution |
| October 30 |
Bernoulli and binomial distributions Reading: Close Quarters |
| November 2 |
Error-correcting codes, Poisson distribution Reading: BT 3.1-3.2 |
| November 4 | Conditional expectation; continuous random variables |
| November 6 |
Expected value; uniform distribution, exponential distribution Reading: BT 3.3 |
| November 9 |
Normal distribution Reading: BT 7.4 |
| November 16 |
Central Limit Theorem Demo |
| November 18 |
Examples of Central Limit Theorem Reading: BT 7.1 |
| November 20 |
Markov, Chebyshev, and Chernoff inequalities Reading: BT 7.2, 7.5 |
| November 23 |
Law of large numbers Reading: Maximum likelihood estimators |
| November 25 |
Maximum likelihood estimators Reading: Bias and confidence intervals |
| November 30 | Bias |
| December 2 | Confidence intervals |
| December 4 | Student's t-distribution |
| December 7 | Probabilistic algorithms: Quicksort |
| December 9 |
Probabilistic algorithms: matrix multiplication Freivalds' algorithm |
| December 11 | Final exam review |