Introduction
So you think you can count?
Combinations and Binomial Coefficients
Inclusion-Exclusion, Pigeonhole Principle and More
Conditional Probability
Bayes Theorem
Bayesian Inference & Independence
Intro to Random Variables & Expectation
Conditional Probabilities, Chain rule
Variance
Independence of RVs
Discrete Random Variables
Continuous RV Basics
Uniform RVs
Expectation & Variance of Continuous RVs
Exponential RVs
Normal Distribution
Central Limit Theorem
Continuity correction
Application: Distinct Elements
Central Limit Theorem
Joint Distributions
Joint Distributions
Tail Bounds:
Markov's Inequality
Chebyshev's Inequality
Chernoff Bounds
Chernoff Bound
Union Bound
Maximum Likelihood Estimation
Maximum Likelihood Estimation
continued
No Lecture: Thanksgiving Holiday
No Section: Thanksgiving Holiday
No Lecture: Thanksgiving Holiday
Informtion Theory & Victory Lap
The final exam is scheduled at 2:30-4:20 pm in our regular classroom (ARC 147).
This course website heavily follows the example of the website of CSE373 2019 Spring.