Data 140: Probability for Data Science
UC Berkeley, Fall 2024
Ani AdhikariProfessor
adhikari
Week 6
 The Week 6 Study Guide has been released.
 Homework 6 and Lab 4 have been released. They are both due next Monday, October 7th at 5 PM.
Calendar
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
 MegaSection
Week 2: Random Variables and Symmetry
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
 MegaSection
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
 MegaSection
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
 MegaSection
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
 Oct 2
 Section
 Oct 3

 Lecture Markov Chain Monte Carlo
 Ch 11.2  11.3
 Oct 4
 MegaSection
Week 7: Variance and Tail Bounds
Week 8: Central Limit Theorem and Densities
Week 9: Transformations and Joint Densities
Week 10: The Beta, Normal, and Gamma Families
Week 11: MGFs, MLE, and MAP
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
 MegaSection
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
 MegaSection
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