Spring 2018 - STAT 380 D100
Introduction to Stochastic Processes (3)
Class Number: 4392
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
- Discrete Time Markov Chains
- Poisson Processes
- Continuous Time Markov Chains
- Some applications
Students should feel comfortable in some programming environment, such as R.
- Assignments 25%
- Midterm 25%
- Final Exam 50%
Above grading is subject to change.
Introduction to Probability Models (11th Edition) by: S.M. Ross. Publisher: Academic Pres
Department Undergraduate Notes:
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