Date |
Syllabus |

3/2 |
Course Overview |

3/4 |
Sets |

3/9 |
Probability Models |

3/11 |
Conditional Probability |

3/16 |
Total Probability Theorem, Bayes' rule and Independence |

3/18 |
Independence of Events & Counting |

3/23 |
Quiz 1 |

3/25 |
Discrete Random Variable Basics and Probability Mass Functions |

3/30 |
Functions of Random Variables & Expectation, Mean and Variance |

4/1 |
Discussion on Quiz 1 |

4/6 |
Joint PMFs of Multiple Random Variables & Conditioning |

4/8 |
Independence |

4/13 |
Continuous Random Variable Basics and PDFs & Cumulative Distribution Functions |

4/15 |
Quiz 2 |

4/20 |
Normal Random Variables & Joint PDFs of Multiple Random Variables |

4/22 |
Discussion on Quiz 2 |

4/27 |
Midterm |

4/29 |
Conditioning |

4/29 |
The Continuous Bayes' Rules
Derived Distributions |

5/4 |
Break for ICASSP2020 |

5/6 |
Break for ICASSP2020 |

5/11 |
Quiz 3 |

5/13 |
Covariance and Correlation & Conditional Expectation and Variance Revisited |

5/18 |
Transforms |

5/20 |
Discussion on Quiz 3 |

5/25 |
Discrete-Time Markov Chains |

5/27 |
Classification of States |

6/1 |
Quiz 4 |

6/3 |
Continuous-Time Markov Chains |

6/8 |
TBD |

6/10 |
Discussion on Quiz 4 |

6/15 |
Final Exam |