LEC # | TOPICS | KEY DATES |
---|---|---|
1 | Probability models and axioms | Problem set 1 out |
2 | Conditioning and Bayes' rule | |
3 | Independence |
Problem set 1 due Problem set 2 out |
4 | Counting | |
5 | Discrete random variables; probability mass functions; expectations |
Problem set 2 due Problem set 3 out |
6 | Discrete random variable examples; joint PMFs | |
7 | Multiple discrete random variables: expectations, conditioning, independence |
Problem set 3 due Problem set 4 out |
8 | Continuous random variables | |
9 | Multiple continuous random variables |
Problem set 4 due Problem set 5 out |
Quiz 1 (covers lectures 1-7) | ||
10 | Continuous Bayes rule; derived distributions | |
11 | Derived distributions; convolution; covariance and correlation |
Problem set 5 due Problem set 6 out |
12 | Iterated expectations; sum of a random number of random variables | |
13 | Bernoulli process | |
14 | Poisson process - I |
Problem set 6 due Problem set 7 out |
Quiz 2 (covers up to lecture 12) | ||
15 | Poisson process - II | |
16 | Markov chains - I |
Problem set 7 due Problem set 8 out |
17 | Markov chains - II | |
18 | Markov chains - III |
Problem set 8 due Problem set 9 out |
19 | Weak law of large numbers | |
20 | Central limit theorem |
Problem set 9 due Problem set 10 out |
21 | Bayesian statistical inference - I | |
22 | Bayesian statistical inference - II | |
23 | Classical statistical inference - I |
Problem set 10 due Problem set 11 out (not to be handed in) |
24 | Classical inference - II | |
25 | Classical inference - III; course overview |