Math 170A: General Course Outline
Catalog Description
    170A. Probability Theory. (4) Lecture, three hours; discussion, one hour. Requisites: courses 32B, 33A. Not open to students with credit for Electrical Engineering 131A or Statistics 100A. Probability distributions, random variables and vectors, expectation. P/NP or letter grading.
Textbook

    Introduction to Probability by D. P. Bertsekas and John N. Tsitsiklis, 2nd edition

    Comments:

    The theoretical problems, which appear with full solutions at the ends of the chapters, are an essential part of the course. Many of them should be incorporated into the lectures.

    Unfortunately, solutions to all of the other problems are freely available on the book’s web site. Additional problems (with no posted solutions) are available at http://www.athenasc.com/prob-supp.html
Schedule of Lectures

Lecture
Section
Topics & Example Numbers
   
Sample Space and Probability
1 1.1 Sets
2-3 1.2 Probabilistic Models
4-5 1.3 Conditional Probability
6 1.4 Total Probability Theorem and Bayes Rule
7-8 1.5 Independence
9 1.6 Counting
10   Midterm Exam
     
    Discrete Random Variables
11-12 2.1, 2.2 Discrete Random Variables; Probability Mass Functions
13-14 2.3, 2.4 Functions of Random Variables; Expectation and Variance
15 2.5, 4.2 Joint PMFs of Multiple Random Variables; Covariance in the Computation of the Variance of a Sum
16-17 2.6 Conditioning
18-19 2.7 Independence
20   Midterm Exam
     
    General Random Variables
21-22 3.1 Continuous Random Variables and PDFs
23 3.2 Cumulative Distribution Functions
24 3.3 Normal Random Variables
25 3.4 Joint PDFs of Multiple Random Variables
26-27 3.5 Conditioning
28 3.6 The Continuous Bayes Rule

Outline T. Liggett 4/10
For more information, please contact Student Services, ugrad@math.ucla.edu.
 

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