EE 364: Introduction to Probability and Statistics for EE/CS

University of Southern California, Spring 2026

Schedule

Week 1

Jan 13

Lecture 1 Introduction to probability. Logic and sets. Probability axioms. Demo Demos Homework 1 Homework 1

Week 2

Jan 20

Lecture 2 Independence. Conditional probability. Bayes' Theorem. Demo Demos Homework 2 Homework 2

Week 3

Jan 27

Lecture 3 Combinatorics. Binomial and multinomial probability. Demo Demos Homework 3 Homework 3

Week 4

Feb 3

Lecture 4 Discrete probability and mass functions. Poisson Theorem. Demo Demos Homework 4 Homework 4

Week 5

Feb 10

Exam Midterm 1 Lecture 4b Poisson Law. Approximations. Handout BEG-CUP pdfs

Week 6

Feb 17

Lecture 5 Continuous probability densities. Homework 5 Homework 5

Week 7

Feb 24

Lecture 5b Cauchy, Gamma, Chi-square, Beta. Demo Demos Homework 6 Homework 6

Week 8

Mar 3

Lecture 6 Expectation, variance, moments.

Week 9

Mar 10

Exam Midterm 2 Lecture 7 Transformed random variables. Demo Demos Homework 7 Homework 7

No class, Spring Break.

Week 10

Mar 24

Lecture 10 Multiple random variables. Covariance and correlation. Uncertainty principles. Demo Demos Homework 8 Homework 8

Week 11

Mar 31

Lecture 11 Stochastic Convergence. Laws of large numbers. Demo Demos Homework 9 Homework 9

Week 12

Apr 7

Lecture 12 Mean square error. Variance-bias decomposition. Lecture 12A Bayesian statistics and conjugacy. Demo Demos

Week 13

Apr 14

Exam Midterm 3 Lecture 13 Conditional expectation. Conditional variance. Demo Demos Homework 10 Homework 10

Week 14

Apr 21

Lecture 14 Confidence intervals. Central limit theorem. Demo Demos

Week 15

Apr 28

Lecture 15 Transforms. Sample mean and sample variance. Homework 11 Homework 11

Final Exam - Thursday, May 7, 16:30 - 18:30