Prob 140 · Probability for Data Science

Week 0 Overview

Getting Started

Before January 21

Week 1

Introduction

1/20-1/24

Week 2

Symmetry and random counts

1/27-1/31

Week 3

Poissonization and Expectation

2/3-2/7

Week 4

Expectation and conditioning

2/10-2/14

Week 5

Markov Chains

2/17-2/21

Week 6

MCMC

2/24-2/28

Week 7

Midterm and Variance

3/2-3/6

Week 8

Covariance; Central Limit Theorem

3/9-3/13

Week 9

Continuous Distributions

3/16-3/20

Week

Spring Break

3/23-3/27

Week 10

The Normal and Gamma Families

3/30-4/3

Week 11

MGFs, MLE, and the Beta Family

4/6-4/10

Week 12

MAP and Beta-Binomial

4/13-4/17

Week 13

Prediction and the multivariate normal

4/20-4/24

Week 14

Correlation and regression

4/27-5/1

Week 16

RRR Week

5/4-5/8

Week 17

Finals Week

5/11-5/15

Week	Date	Content	Prep & Assignments
1	Tues 1/21	Lecture 1: Probability — axioms, rules, approximation	Weeks 1 & 2 Guide Lab 1: Simple Random Samples (Due 1/26 at 12:00PM noon) HW 1 (Due 1/28 at 12:00PM noon)
	Wed 1/22	Discussion
	Thurs 1/23	Lecture 2: Random variables — distributions, equality, conditioning
	Fri 1/24	Discussion
2	Tue 1/28	Lecture 3: Symmetry and collections of events	Weeks 1 & 2 Guide Lab 2:Total Variation (Due 2/2 at 12:00PM noon) HW 2 (Due 2/4 at 12:00PM noon)
	Wed 1/29	Discussion
	Thu 1/30	Lecture 4: Binomial and related counts; a Poisson limit
	Fri 1/31	Discussion
3	Tue 2/4	Lecture 5: Independence and Poissonization	Weeks 3 & 4 Guide Lab 3: Expectation of Discrete Order Statistics (Due 2/9 at 12:00PM noon) HW 3 (Due 2/11 at 12:00PM noon)
	Wed 2/5	QUIZ 1
	Thu 2/6	Lecture 6: Expectation
	Fri 2/7	Discussion
4	Tue 2/11	Lecture 7: Expectation and additivity	Weeks 3 & 4 Guide Lab 4: Success Runs and Other Patterns (Due 2/23 at 12:00PM noon) HW 4 (Due 2/18 at 12:00PM noon)
	Wed 2/12	Discussion
	Thu 2/13	Lecture 8: Expectation by conditioning
	Fri 2/14	Discussion
5	Tue 2/18	Lecture 9: Long run behavior of Markov Chains	Weeks 5 & 6 Guide Lab 4: Success Runs and Other Patterns (Due 2/23 at 12:00PM noon) Homework 5 (Due 2/25 at 12:00PM noon)
	Wed 2/19	Discussion
	Thu 2/20	Lecture 10: Balance
	Fri 2/21	Discussion
6	Tue 2/25	Lecture 11: Markov Chain Monte Carlo
	Wed 2/26	Discussion
	Thu 2/27	Lecture 12: Examples as review
	Fri 2/28	Discussion
7	Tue 3/3	MIDTERM
	Wed 3/4	No Discussion
	Thu 3/5	Lecture 13: SD, tail bounds
	Fri 10/11	Discussion
8	Tue 3/10	Lecture 14: Covariance and its uses
	Wed 3/11	Discussion
	Thu 3/12	Lecture 15: Central Limit Theorem
	Fri 3/13	Discussion
9	Tue 3/17	Lecture 16: Probability densities
	Wed 3/18	Discussion
	Thu 3/19	Lecture 17: Transformations
	Fri 3/20	Discussion
	Tue 3/24
	Wed 3/25
	Thu 3/26
	Fri 3/27
10	Tue 3/31	Lecture 18: Joint densities
	Wed 4/1	QUIZ 2
	Thu 4/2	Lecture 19: Independent normal and gamma variables
	Fri 4/3	Discussion
11	Tue 4/7	Lecture 20: Moment generating functions; Chernoff bound
	Wed 4/8	Discussion
	Thu 4/9	Lecture 21: MLE; the beta family
	Fri 4/10	Discussion
12	Tue 4/14	Lecture 22: Conditioning; MAP estimates
	Wed 4/15	QUIZ 3
	Thu 4/16	Lecture 23: The beta and the binomial
	Fri 4/17	Discussion
13	Tue 4/21	Lecture 24: Prediction and error
	Wed 4/22	Discussion
	Thu 4/23	Lecture 25: Random vectors; multivariate normal
	Fri 4/24	Discussion
14	Tue 4/28	Lecture 26: Correlation and simple regression
	Wed 4/29	Discussion
	Thu 4/30	Lecture 27: Multiple regression
	Fri 5/1	Discussion
16	Tue 5/5
17	Fri 5/15	FINAL EXAM (7PM to 10PM)