Course: MATH 170A, Probability Theory, Lecture 3, Winter 2016
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: 15 March 2016

Instructor: Steven Heilman, heilman(@-symbol)
Office Hours: Mondays 10AM-11AM, Fridays, 9AM-10AM, MS 5634
Lecture Meeting Time/Location: Monday, Wednesday and Friday, 1PM-150PM, MS 6229
TA: Adam Haque, adamhaque12(@-symbol)
TA Office Hours:Wednesdays 4PM-5PM, Thursdays, 10AM-11AM, 2PM-3PM, MS 3975
Discussion Session Meeting Time/Location: Thursday, 1PM-150PM MS 6229
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, January 29th, 1PM-150PM, Pub Aff 2214
Second Midterm: Monday, February 22nd, 1PM-150PM, Bunche 1209B
Final Exam: Tuesday, March 15, 8AM-11AM, KNSY PV 1200B
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 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
1Jan 4: 1.1, Sets Jan 6: 1.2, Probabilistic Models Jan 7: Homework 0 (ungraded) Jan 8: 1.2, Probabilistic Models
2 Jan 11: 1.3, Conditional Probability Jan 13: 1.3, Conditional Probability Jan 14: Homework 1 due Jan 15: 1.4, Total Probability Theorem and Bayes' Rule
3 Jan 18: No class Jan 20: 1.5, Independence Jan 21: Homework 2 due Jan 22: 1.5, Independence
4 Jan 25: 1.6, Counting Jan 27: 2.1, Discrete Random Variables Jan 28: Homework 3 due Jan 29: Midterm #1
5 Feb 1: 2.2, Probability Mass Function Feb 3: 2.3, Functions of Random Variables Feb 4: Homework 4 due Feb 5: 2.4, Expectation and Variance
6 Feb 8: 2.5, Joint PMFs, Covariance and Variance Feb 10: 2.6, Conditioning Feb 11: Homework 5 due Feb 12: 2.6, Conditioning
7 Feb 15: No class Feb 17: 2.7, Independence Feb 18: Homework 6 due Feb 19: 2.7, Independence
8 Feb 22: Midterm #2 Feb 24: 3.1, Continuous random variables and PDFs Feb 25: No homework dueFeb 26: 3.1, Continuous random variables and PDFs
9 Feb 29: 3.2, Cumulative Distribution Functions Mar 2: 3.3, Normal Random Variables Mar 3: Homework 7 due Mar 4: 3.4, Joint PDFs of Multiple Random Variables
10 Mar 7: 3.5, Conditioning Mar 9:3.5, ConditioningMar 10: Homework 8 due Mar 11: 3.6, The Continuous Bayes Rule

Advice on succeeding in a math class:

Homework Exam Solutions Supplementary Notes