Course: MATH 170A, Probability Theory, Lecture 2, Spring 2017
Prerequisite: Math 32B and Math 33A. Not open to students with credit for Electrical Engineering 131A or Statistics 100A.
Course Content: Probability distributions, random variables and vectors, expectation.
Last update: 14 June 2017

Instructor: Steven Heilman, heilman(@-symbol)
Office Hours: Fridays, 9AM-11AM, MS 5634
Lecture Meeting Time/Location: Monday, Wednesday and Friday, 1PM-150PM, MS 5127
TA: Tianqi Wu, timwu(@-symbol)
TA Office Hours: Thursdays 3PM-5PM, MS 6146
Discussion Session Meeting Time/Location: Tuesday, 1PM-150PM, MS 5127
Required Textbook: D. P. Bertsekas and John N. Tsitsiklis, Introduction to Probability, 2nd edition. (The book is freely available online, though some sections are ordered differently than the textbook.)
Other Textbooks (not required): Elementary Probability for Applications, Durrett. (or a more advanced text for someone who has at least taken 115a and 131a:) Probability: Theory and Examples, Durrett.
First Midterm: Friday, April 28, 1PM-150PM, Broad 2100A
Second Midterm: Monday May 22, 1PM-150PM, MS 5127
Final Exam:Tuesday, June 13, 8AM-11AM, Boelter 2444
Other Resources: Supplemental Problems from the textbook. An introduction to mathematical arguments, Michael Hutchings, An Introduction to Proofs, How to Write Mathematical Arguments
Email Policy:

Exam Procedures: Students must bring their UCLA ID cards to the midterms and to the final exam. Phones must be turned off. Cheating on an exam results in a score of zero on that exam. Exams can be regraded at most 15 days after the date of the exam. This policy extends to homeworks as well. All students are expected to be familiar with the UCLA Student Guide to Academic Integrity. If you are an OSD student, I would encourage you to discuss with me ways that I can improve your learning experience; I would also encourage you to contact the OSD office to confirm your exam arrangements at the beginning of the quarter.
Exam Resources: Here are the exams I used when I taught this course in previous quarters: Exam 1 Exam 1 Solutions Exam 2 Exam 2 Solutions. Final Final Solutions. Exam 1 Exam 1 Solutions Exam 2 Exam 2 Solutions. Final Final Solutions. Here is a page containing old exams for another 170A class. Here is a 170A practice midterm (with solutions). Here is a 170A practice second midterm. Here is a 170A practice final. Occasionally these exams will cover slightly different material than this class, or the material will be in a slightly different order, but generally, the concepts should be close if not identical.

Homework Policy: Grading Policy:

Tentative Schedule: (This schedule may change slightly during the course.)

Week Monday Tuesday Wednesday Thursday Friday
1Apr 3: 1.1, Sets Apr 4: Homework 0 (ungraded) Apr 5: 1.2, Probabilistic Models Apr 7: 1.2, Probabilistic Models
2 Apr 10: 1.3, Conditional Probability Apr 11: Homework 1 due Apr 12: 1.3, Conditional Probability Apr 14: 1.4, Total Probability Theorem and Bayes' Rule
3 Apr 17: 1.5, Independence Apr 18: Homework 2 due Apr 19: 1.5, Independence Apr 21: 1.6, Counting
4 Apr 24: 2.1, Discrete Random Variables Apr 25: Homework 3 due Apr 26: 2.2, Probability Mass Function Apr 28: Midterm #1
5 May 1: 2.3, Functions of Random Variables May 2: Homework 4 due May 3: 2.4, Expectation and Variance May 5, 2.5, Joint PMFs, Covariance and Variance
6 May 8: 2.6, Conditioning May 9, Homework 5 due May 10: 2.6, Conditioning May 12: 2.7, Independence
7 May 15, 2.7, Independence May 16: Homework 6 due May 17: 3.1, Continuous random variables and PDFs May 19: 3.1, Continuous random variables and PDFs
8 May 22: Midterm #2 May 23: No homework due May 24: 3.2, Cumulative Distribution Functions May 26: 3.3, Normal Random Variables
9 No class May 30: Homework 7 due Jun 1: Joint PDFs of Multiple Random Variables Jun 3: 3.5, Conditioning
10 Jun 5: 3.5, Conditioning Jun 6: Homework 8 due Jun 7: The Continuous Bayes Rule Jun 9, Review of Course

Advice on succeeding in a math class:

Homework Exam Solutions Supplementary Notes