Stochastic processes are mathematical models for random phenomena evolving in time or space. This course will introduce important examples of such models, including random walk, branching processes, the Poisson process and Brownian motion. The theory of Markov chains in discrete and continuous time will be developed as a unifying theme. Depending on time available and interests of the class, applications will be selected from the following areas: queuing systems, mathematical finance (Black-Scholes options pricing), probabilistic algorithms, and Monte Carlo simulation. (MATH 0310) 3 hrs. lect./disc.
- Spring 2013
- Warner Hall 207(WNS 207)
- 10:10am-11:00am on Monday, Wednesday, Friday (Feb 11, 2013 to May 13, 2013)
- William Peterson
- Natural Sciences
- Requirements Fulfilled:
- View availability, prerequisites, and other requirements.
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