CS2008301: Probability and Statistics

Lecture: Monday, 13:20~15:10 & Wensday, 15:30~16:20

 

Instructor: at

Teaching Assistants:

 

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