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MTHE 455 Stochastic Processes & Applications Units: 3.50
Markov chains, birth and death processes, random walk problems, elementary renewal theory, Markov processes, Brownian motion and Poisson processes, queuing theory, branching processes.
(Lec: 3, Lab: 0, Tut: 0.5)
(Lec: 3, Lab: 0, Tut: 0.5)
Requirements: Prerequisites: MTHE 353 (STAT 353) or one of STAT 251, MTHE 351 (STAT 351), ELEC 326 with permission of the instructor
Corequisites:
Exclusions:
Offering Term: F
CEAB Units:
Mathematics 28
Natural Sciences 0
Complementary Studies 0
Engineering Science 14
Engineering Design 0
Offering Faculty: Faculty of Arts and Science
Course Learning Outcomes:
- Compute an expectation using conditioning.
- Convert a process description into a Markov chain model.
- Understand the mathematical structure of a Markov chain.
- Identify the stationary distribution of Markov chains.
- Prove results about Markov chains.
- Compute an expectation using Markov Chain Monte Carlo.