Course Description
Modern introduction to Probability Theory and Stochastic Processes. The choice of material is motivated by applications to problems such as queueing networks, filtering and financial mathematics. Topics include: review of discrete probability and continuous random variables, random walks, markov chains, martingales, stopping times, erodicity, conditional expectations, continuous-time Markov chains, laws of large numbers, central limit theorem and large deviations.
Fall 2024
Instructors
Meeting Patterns
Classes Start:
August 19, 2024
Classes End:
December 3, 2024
Location:
02102 SAS Hall
Class Days:
T H
Class Start Time:
11:45am
Class End Time:
1:00pm
Class Type:
Lecture
Credits:
3.00
Restrictions:
Prerequisite: MA 421 and MA 425 or MA 511 R: Statistics Graduate Students Only
