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 and foundations, generating functions, random walks, branching processes, Markov chains and continuous time Markov processes. The ideas and methods in this course have wide applicability in mathematics, computer science, virtually all the sciences, engineering, economics and management.
Instructor: L. Pakula, Tyler 201, X4519, pakula@math.uri.edu
Text: Grimmett and Stirzaker, Probability and Random Processes, 3rd Edition
Time: MW 3-4:15
NOTE! The Final Exam will be on Thu Dec. 21 at 3 PM in Washburn 308 (our regular classroom for the course)
Room: Washburn 308
Abel and continuity theorems handout
Maple worksheet simulates random walk
Maple worksheet on simulation and empirical distribution functions
Page readings in text: 1-14; 17-18; 26-30; 33-34;46-59; 318; 320-321; 60-70; 148-154; 162-165;171-175;181-184; 186-194; 122-125; Sections 6.1-6.4, 6.5,6.14,6.8,6.9 (selections),13.2,13.3 (selections, not covered on final)