6.041 | Fall 2010 | Undergraduate

# Probabilistic Systems Analysis and Applied Probability

## 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

## Course Info

Fall 2010
##### Learning Resource Types
Problem Sets with Solutions
Exams with Solutions
Lecture Videos