MA 509: Stochastic Modeling

Credits 3.0
This course gives students a background in the theory and methods of probability, stochastic processes and statistics for applications. The course begins with a brief review of basic probability, discrete and continuous random variables, expectations, conditional probability and basic statistical inference. Topics covered in greater depth include generating functions, limit theorems, basic stochastic processes, discrete and continuous time Markov chains, and basic queuing theory including M/M/1 and M/G/l queues. This course is offered by special arrangement only, based on expressed student interest.
Prerequisites

knowledge of basic probability at the level of MA 2631 and statistics at the level of MA 2612 is assumed.