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 |