This is a second course in probability theory. Prerequisites are MTH 451 (Probability) or an equivalent course, linear algebra, and some advanced calculus. Emphasis will be placed on fundamental principles, thinking probabilistically, and ``tricks of the trade.'' Topics will include: a second look at basic probability theory, generating functions and recurrences, random walks, branching processes, Markov chains and Markov processes. The ideas and methods in this course have wide applicability in mathematics, computer science, virtually all the sciences, engineering, economics and management.
Maple worksheet on empirical d.f.'s and simulation
Matlab m-file for plotting empirical d.f.s
Instructor: L. Pakula, Tyler 201, X4519, pakula@math.uri.edu
Text: Grimmett and Stirzaker, Probability and Random Processes, 2nd Edition
Time: MW 2-3:45
Room: