Data 140: Probability for Data Science

UC Berkeley, Spring 2024

Ani AdhikariProfessor

adhikari

Week 9

Mar 11

Calendar

Jump to current week

Week 1: Introduction

Jan 16
Lecture Probability: axioms, rules, approximation
Course Information, Ch 1, 2
Guide Week 1
Homework Homework 1
Due Jan 22 at 5PM
Lab Lab 1
Due Jan 22 at 5PM
Jan 17
Section
Jan 18
Lecture Random variables: distributions, equality, conditioning
Ch 3, 4
Jan 19
Mega-Section

Week 2: Symmetry and Random Counts

Jan 22
Guide Week 2
Homework Homework 2
Due Jan 29 at 5PM
Lab Lab 2
Due Jan 29 at 5PM
Jan 23
Lecture Symmetry and collections of events
Ch 5
Jan 24
Section
Jan 25
Lecture Binomial and related counts; a Poisson limit
Ch 6
Jan 26
Mega-Section

Week 3: Poissonization and Expectation

Jan 29
Guide Week 3
Homework Homework 3
Due Feb 5 at 5PM
Lab Lab 3A
Due Feb 5 at 5PM
Jan 30
Lecture Independence and Poissonization
Ch 7
Jan 31
Section
Feb 1
Lecture Expectation
Ch 8.1 - 8.3
Feb 2
Mega-Section

Week 4: Expectation and Conditioning

Feb 5
Guide Week 4
Homework Homework 4
Due Feb 12 at 12 noon
Lab Lab 3B
Due Feb 12 at 12 noon
Feb 6
Lecture Expectation and additivity
Ch 8.4 - 8.5
Feb 7
Section
Feb 8
Lecture Expectation by conditioning
Ch 9
Feb 9
Mega-Section

Week 5: Markov Chains

Feb 12
Exam Midterm 1
7PM - 9PM
Feb 13
Guide Week 5
Homework Homework 5
Due Feb 20 at 12 noon
Lecture Long run behavior of Markov chains
Ch 10
Feb 14
Section
Feb 15
Lecture Balance
Ch 10, 11.1
Feb 16
Mega-Section

Week 6: MCMC and Variance

Feb 20
Guide Week 6
Homework Homework 6
Due Feb 26 at 5PM
Lab Lab 4
Due Feb 26 at 5PM
Lecture Markov Chain Monte Carlo
Ch 11.2 - 11.3
Feb 21
Section
Feb 22
Lecture Standard deviation and tail bounds
Ch 12
Feb 23
Mega-Section

Week 7: Covariance and CLT

Feb 26
Guide Week 7
Homework Homework 7
Due Mar 4 at 5PM
Lab Lab 5
Due Mar 4 at 5PM
Feb 27
Lecture Covariance and its uses
Ch 13
Feb 28
Section
Feb 29
Lecture Central Limit Theorem
Ch 14
Mar 1
Mega-Section

Week 8: Densities and Transformations

Mar 4
Guide Week 8
Homework Homework 8
Due Mar 11 at 5PM
Lab Lab 6A
Due Mar 11 at 5PM
Mar 5
Lecture Probability densities
Ch 15
Mar 6
Section
Mar 7
Lecture Transformations
Ch 16
Mar 8
Mega-Section

Week 9: Joint Densities, Beta, Normal, and Gamma Families

Mar 11
Guide Week 9
Homework Homework 9
Due Mar 18 at 12 noon
Lab Lab 6B
Due Mar 18 at 12 noon
Mar 12
Lecture Joint densities
Ch 17
Mar 13
Section
Mar 14
Lecture Joint distributions; sums of normal and gamma variables
Ch 17, Ch 18
Mar 15
Mega-Section

Week 10: MGFs

Mar 18
Exam Midterm 2
7PM - 9PM
Mar 19
Guide Week 10
Homework Homework 10
Lecture Moment generating functions
Ch 19
Mar 20
Section
Mar 21
Lecture Moment generating functions; Chernoff bound
Ch 19

Week 11: Spring Break

Mar 25
Spring Break
Mar 26
Spring Break
Mar 27
Spring Break
Mar 28
Spring Break
Mar 29
Spring Break

Week 12: MLE, MAP, the Beta and the Binomial

Apr 1
Homework Homework 11
Due Apr 8 at 5PM
Apr 2
Lecture MLE; conditioning; MAP estimates
Ch 20
Apr 3
Section
Apr 4
Lecture The beta and the binomial
Ch 21
Apr 5
Mega-Section

Week 13: Prediction and Error

Apr 8
Homework Homework 12
Due Apr 15 at 5PM
Apr 9
Lecture Prediction and error
Ch 22.1 - 22.2
Apr 10
Section
Apr 11
Lecture Variance by conditioning
Ch 22.3 - 22.4
Apr 12
Mega-Section

Week 14: Random Vectors and Simple Regression

Apr 15
Homework Homework 13
Due Apr 22 at 5PM
Apr 16
Lecture Random vectors; the multivariate normal
Ch 23
Apr 17
Section
Apr 18
Lecture Correlation and simple regression
Ch 24
Apr 19
Mega-Section

Week 15: Multiple Regression

Apr 22
Homework Homework 14
Due Apr 29 at 5PM
Apr 23
Lecture Multiple regression I
Ch 25.1 - 25.3
Apr 24
Section
Apr 25
Lecture Multiple regression II
Ch 25.4
Apr 26
Mega-Section

Week 16: Reading, Review, Recitation

Apr 29
RRR Week
Apr 30
RRR Week
May 1
RRR Week
May 2
RRR Week
May 3
RRR Week

Week 17: Final Exams

May 6
Exam Final Exam
11:30AM - 2:30PM