Spring 2022 - STAT 380 D100
Introduction to Stochastic Processes (3)
Class Number: 6717
Delivery Method: In Person
Review of discrete and continuous probability models and relationships between them. Exploration of conditioning and conditional expectation. Markov chains. Random walks. Continuous time processes. Poisson process. Markov processes. Gaussian processes. Quantitative.
- Review: Chapters 1,2,3 of text
- Discrete Time Markov Chains
- Poisson Processes
- Continuous Time Markov Chains
- Applications to Queuing and Renewal Theory
- Introduction to Brownian Motion and Diffusion
- Monte Carlo Simulation
Students should feel comfortable in some programming environment, preferably R because I will be giving assignments and doing examples in R.
- Assignments 30%
- Midterms (Date: Wednesday, February 9th, and Wednesday, March 16th, 2022) 30%
- Final Exam 40%
Above grading is subject to change.
Introduction to Probability Models (12th Edition) by: S.M. Ross. Publisher: Academic Press
Book is available through the SFU Bookstore
Department Undergraduate Notes:
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ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS
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TEACHING AT SFU IN SPRING 2022
Teaching at SFU in spring 2022 will involve primarily in-person instruction, with safety plans in place. Some courses will still be offered through remote methods, and if so, this will be clearly identified in the schedule of classes. You will also know at enrollment whether remote course components will be “live” (synchronous) or at your own pace (asynchronous).
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Students with hidden or visible disabilities who may need class or exam accommodations, including in the context of remote learning, are advised to register with the SFU Centre for Accessible Learning (email@example.com or 778-782-3112) as early as possible in order to prepare for the spring 2022 term.