Calendar

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