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STAT 455  Stochastic Processes and Applications  Units: 3.00  
Markov chains, birth and death processes, random walk problems, elementary renewal theory, Markov processes, Brownian motion and Poisson processes, queuing theory, branching processes.
NOTE This course is also listed/offered as MATH 455/3.0.
Learning Hours: 120 (36 Lecture, 12 Tutorial, 72 Private Study)  
Requirements: Prerequisite STAT 353/3.0. Exclusion MATH 455/3.0.  
Offering Faculty: Faculty of Arts and Science  

Course Learning Outcomes:

  1. Computing an expectation using conditioning.
  2. Computing an expectation using Markov Chain Monte Carlo.
  3. Converting a process description into a Markov chain model.
  4. Identifying the stationary distribution of Markov chains.
  5. Proving results about Markov chains.
  6. Understanding the mathematical structure of a Markov chain.