CS2008301: Probability and Statistics

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

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