Date	Description
March 27	Overview Reading: BT 1.1, 1.2, 1.6, Intro to Schnapsen, Rules of Schnapsen Notes, HW1 LaTeX source
March 29	Counting: product rule, permutations Reading: Safety First (Schnapsen analysis) Trick mechanics, Notes
March 31	Counting: combinations Notes
April 3	Counting: complementing, inclusion-exclusion, pigeonhole principle Notes
April 5	Intro to probability; equiprobable outcomes Reading: BT 1.3 Notes, HW2 LaTeX source
April 7	Conditional probability Reading: BT 1.5 Notes
April 10	Law of Total Probability Reading: BT 1.4 Notes
April 12	Bayes' Theorem Notes, HW3 LaTeX source
April 14	Independent events Reading: BT 2.1-2.3 Notes
April 17	Naive Bayes classifier Reading: Naive Bayes notes Naive Bayes slides, Notes
April 19	Random variables, expectation, geometric random variable Reading: BT 2.4, Expected Game Points, last year's exercise Notes, HW4 LaTeX source
April 21	Linearity of expectation Reading: BT 2.7 Notes
April 24	Variance Notes
April 26	Independent random variables Notes
April 28	Uniform, Bernoulli, and binomial distributions Notes, HW5 LaTeX source
May 1	Error-correcting codes, Poisson distribution Reading: BT 3.1-3.2
May 5	Midterm debrief; continuous random variables Reading: BT 3.3 Notes
May 8	Uniform, exponential distributions Reading: BT 7.4 Notes, HW6 LaTeX source
May 10	Normal distribution, Central Limit Theorem Demo
May 12	Applications of Central Limit Theorem Reading: BT 7.1
May 15	Examples of Central Limit Theorem Notes, HW7 LaTeX source
May 17	Markov, Chebyshev, and Chernoff inequalities Reading: BT 7.2, 7.5 Notes
May 19	Law of large numbers Reading: Maximum likelihood estimators Notes
May 22	Maximum likelihood estimators Reading: Bias and confidence intervals Notes, HW8 LaTeX source
May 24	Bias Notes
May 26	Confidence intervals Notes
May 31	Probabilistic algorithms: Quicksort, matrix multiplication Freivalds' algorithm, Notes
June 2	Final exam review, HW8 solutions Notes