Data 140: Probability for Data Science

UC Berkeley, Fall 2024

Ani AdhikariProfessor

adhikari

Week 6

Sep 30

Calendar

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Week 1: Introduction

Aug 28
Guide Week 1
Aug 29
Lecture Probability: axioms, rules, approximation
Course Information, Ch 1, 2
Homework Homework 1
Due Sep 3 at 9 AM
Lab Lab 1
Due Sep 3 at 9 AM
Aug 30
Mega-Section

Week 2: Random Variables and Symmetry

Sep 2
Labor Day
Guide Week 2
Sep 3
Lecture Random variables: distributions, equality, conditioning
Ch 3, 4
Homework Homework 2
Due Sep 9 at 5 PM
Lab Lab 2
Due Sep 9 at 5 PM
Sep 4
Section
Sep 5
Lecture Symmetry and collections of events
Ch 5
Sep 6
Mega-Section

Week 3: Random Counts

Sep 9
Guide Week 3
Homework Homework 3
Due Sep 16 at 5 PM
Lab Lab 3A
Due Sep 16 at 5 PM
Sep 10
Lecture Binomial and related counts; a Poisson limit
Ch 6
Sep 11
Section
Sep 12
Lecture Independence and Poissonization
Ch 7
Sep 13
Mega-Section

Week 4: Expectation

Sep 16
Guide Week 4
Homework Homework 4
Due Sep 23 at 5 PM
Lab Lab 3B
Due Sep 23 at 5 PM
Sep 17
Lecture Expectation
Ch 8.1 - 8.3
Sep 18
Section
Sep 19
Lecture Expectation and additivity
Ch 8.4 - 8.5
Sep 20
Mega-Section

Week 5: Conditioning and Markov Chains

Sep 23
Guide Week 5
Homework Homework 5
Due Sep 30 at 12 PM NOON
Sep 24
Lecture Expectation by conditioning
Ch 9
Sep 25
Section
Sep 26
Lecture Long run behavior of Markov chains
Ch 10
Sep 27
Mega-Section

Week 6: Markov Chain Monte Carlo

Sep 30
Exam Midterm 1
8PM - 10PM
Oct 1
Guide Week 6
Homework Homework 6
Due Oct 7 at 5 PM
Lab Lab 4
Due Oct 7 at 5 PM
Lecture Balance
Ch 10, 11.1
Oct 2
Section
Oct 3
Lecture Markov Chain Monte Carlo
Ch 11.2 - 11.3
Oct 4
Mega-Section

Week 7: Variance and Tail Bounds

Oct 7
Oct 8
Lecture Standard deviation and tail bounds
Ch 12
Oct 9
Section
Oct 10
Lecture Covariance and its uses
Ch 13
Oct 11
Mega-Section

Week 8: Central Limit Theorem and Densities

Oct 14
Oct 15
Lecture Central Limit Theorem
Ch 14
Oct 16
Section
Oct 17
Lecture Probability densities
Ch 15
Oct 18
Mega-Section

Week 9: Transformations and Joint Densities

Oct 21
Oct 22
Lecture Transformations
Ch 16
Oct 23
Section
Oct 24
Lecture Joint densities
Ch 17
Oct 25
Mega-Section

Week 10: The Beta, Normal, and Gamma Families

Oct 28
Oct 29
Lecture Joint distributions; sums of normal and gamma variables
Ch 17, Ch 18
Oct 30
Section
Oct 31
Lecture Moment generating functions
Ch 19
Nov 1
Mega-Section

Week 11: MGFs, MLE, and MAP

Nov 4
Exam Midterm 2
8PM - 10PM
Nov 5
Lecture Moment generating functions; Chernoff bound
Ch 19
Nov 6
Section
Nov 7
Lecture MLE; conditioning; MAP estimates
Ch 20
Nov 8
Mega-Section

Week 12: The Beta and the Binomial; Prediction

Nov 11
Veterans Day
Nov 12
Lecture The beta and the binomial
Ch 21
Nov 13
Section
Nov 14
Lecture Prediction and error
Ch 22.1 - 22.2
Nov 15
Veterans Day Holiday

Week 13: Variance by Conditioning and Random Vectors

Nov 18
Nov 19
Lecture Variance by conditioning
Ch 22.3 - 22.4
Nov 20
Section
Nov 21
Lecture Random vectors; the multivariate normal
Ch 23
Nov 22
Mega-Section

Week 14: Simple Regression

Nov 25
Nov 26
Lecture Correlation and simple regression
Ch 24
Nov 27
Thanksgiving Break
Nov 28
Thanksgiving Break
Nov 29
Thanksgiving Break

Week 15: Multiple Regression

Dec 2
Dec 3
Lecture Multiple regression I
Ch 25.1 - 25.3
Dec 4
Section
Dec 5
Lecture Multiple regression II
Ch 25.4
Dec 6
Mega-Section

Week 16: Reading, Review, Recitation

Dec 9
RRR Week
Dec 10
RRR Week
Dec 11
RRR Week
Dec 12
RRR Week
Dec 13
RRR Week

Week 17: Final Exams

Dec 17
Exam Final Exam
3PM - 6PM