Prob 140 · Probability for Data Science

Week 0 Overview

Getting Started

Before January 22

Week 1

Introduction

1/22-1/25

Week 2

Symmetry and Random Counts

1/28-2/1

Week 3

Poissonization; Expectation

2/4-2/8

Week 4

Conditioning and Markov Chains

2/11-2/15

Week 5

MCMC

2/18-2/22

Week 6

Midterm Week

2/25-3/1

Week 7

Variance and Covariance

3/4-3/8

Week 8

Continuous Distributions

3/11-3/15

Week 9

Working with Continuous Distributions

3/18-3/22

Week 10

Spring Break

3/25-3/31

Week 11

The Normal and Gamma Families

4/1-4/5

Week 12

MLE, MAP, and the Beta Family

4/8-4/12

Week 13

Beta-Binomial and Prediction

4/15-4/19

Week 14

Multivariate Normal Distribution

4/22-4/26

Week 15

Regression

4/29-5/3

Week 16

RRR Week

5/6-5/10

Week 17

Finals Week

5/13-5/17

Week	Date	Content	Prep & Assignments
1	Tue 1/22	Lecture 1: Probability — axioms, rules, approximation	Week 1 Guide Lab 1: Birthday Attack (Due 1/26 noon) HW 1 (Due 1/29 noon)
	Wed 1/23	Discussion
	Thu 1/24	Lecture 2: Random variables — distributions, conditioning, equality
	Fri 1/25	Discussion; Supplementary Sections
2	Tue 1/29	Lecture 3: Symmetry and collections of events	Week 2 Guide Lab 2: Total Variation (Due Sat 2/2 noon) HW 2 (Due Tue 2/5 noon)
	Wed 1/30	Discussion
	Thu 1/31	Lecture 4: Binomial and related counts; a Poisson limit
	Fri 2/1	Discussion; Supplementary Sections
3	Tue 2/5	Lecture 5: Independence and Poissonization	Week 3 Guide Lab 3: Expectations of Discrete Order Statistics (Due Sat 2/9 noon) HW 3 (Due Tue 2/12 noon)
	Wed 2/6	QUIZ 1
	Thu 2/7	Lecture 6: Expectation and additivity
	Fri 2/8	Discussion; Supplementary Sections
4	Tue 2/12	Lecture 7: Expectation by conditioning	Week 4 Guide Lab 4: Success Runs and Other Patterns (Due Sun 2/17 noon) HW 4 (Due Tue 2/19 noon)
	Wed 2/13	Discussion
	Thu 2/14	Lecture 8: Long run behavior of Markov Chains
	Fri 2/15	Discussion; Supplementary Sections
5	Tue 2/19	Lecture 9: Balance	Week 5 Guide Midterm Prep Lab 5: Codebreaking by MCMC (Due Sat 2/23 noon) HW 5 (Due Tue 2/26 noon)
	Wed 2/20	Discussion
	Thu 2/21	Lecture 10: Markov Chain Monte Carlo
	Fri 2/22	Discussion; Supplementary Sections
6	Tue 2/26	Lecture 11: Midterm review
	Wed 2/27	Discussion
	Thu 2/28	MIDTERM (in class)
	Fri 3/1	Day Off
7	Tue 3/5	Lecture 12: SD and tail bounds
	Wed 3/6	Discussion
	Thu 3/7	Lecture 13: Covariance and its uses
	Fri 3/8	Discussion; Supplementary Sections
8	Tue 3/12	Lecture 14: Central Limit Theorem
	Wed 3/13	Discussion
	Thu 3/14	Lecture 15: Probability densities
	Fri 3/15	Discussion; Supplementary Sections
9	Tue 3/19	Lecture 16: Transformations
	Wed 3/20	QUIZ 2
	Thu 3/21	Lecture 17: Joint densities
	Fri 3/22	Discussion; Supplementary Sections
10	Tue 3/26	Holiday
	Wed 3/27	Holiday
	Thu 3/28	Holiday
	Fri 3/29	Holiday
11	Tue 4/2	Lecture 18: Independent normal and gamma variables; moment generating functions
	Wed 4/3	Discussion
	Thu 4/4	Lecture 19: CLT revisited; Chernoff bound
	Fri 4/5	Discussion; Supplementary Sections
12	Tue 4/9	Lecture 20: MLE
	Wed 4/10	QUIZ 3
	Thu 4/11	Lecture 21: Beta family; posterior distributions; MAP estimates
	Fri 4/12	Discussion; Supplementary Sections
13	Tue 4/16	Lecture 22: The beta and the binomial
	Wed 4/17	Discussion
	Thu 4/18	Lecture 23: Prediction and error
	Fri 4/19	Discussion; Supplementary Sections
14	Tue 4/23	Lecture 24: Random vectors; the multivariate normal
	Wed 4/24	QUIZ 4
	Thu 4/25	Lecture 25: Properties of the multivariate normal; the bivariate case
	Fri 4/26	Discussion; Supplementary Sections
15	Tue 4/30	Lecture 26: Correlation and simple regression
	Wed 5/1	Discussion
	Thu 5/2	Lecture 27: Multiple regression
	Fri 5/3	Discussion
16	Tue 5/7
	Wed 5/8
	Thu 5/9
	Fri 5/10
17	Tue 5/14
	Wed 5/15
	Thu 5/16
	Fri 5/17	FINAL EXAM (11:30 a.m. to 2:30 p.m.)