STAT 3506
Stochastic Processes and Applications (Honours)
Conditional probability and conditional expectation; Stochastic modeling; discrete time Markov chains including classification of states, stationary and limiting distributions; exponential distribution and the Poisson processes; queueing models; applications to computer systems, operations research and social sciences.
Topics
- classification of states
- stationary and limiting distributions
- exponential distribution and the Poisson processes
- queueing models
- applications to computer systems
- operations research and social sciences
Course catalogue
2021
Readings
- Sheldon Ross, Introduction to Probability Models, 12th Edition, Academic Press, 2019.
Prerequisites & course information
Prerequisite(s): STAT 2655 with a grade of C- or higher; or permission of the School. Lectures three hours a week, tutorial one hour a week.
Sources
- Course catalogue ↗2026–2027
- STAT 3506A W22 ↗2021