MATH0410A-S25
Stochastic Processes
Stochastic Processes
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.
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.
- Term:
- Spring 2025
- Location:
- Warner Hall 011(WNS 011)
- Schedule:
- 8:40am-9:30am on Monday, Wednesday, Friday (Feb 10, 2025 to May 12, 2025)
- Type:
- Lecture
- Course Modality:
- In-Person
- Instructors:
- Bill Peterson
- Subject:
- Mathematics
- Department:
- Mathematics & Statistics
- Division:
- Natural Sciences
- Requirements Fulfilled:
- DED
- Levels:
- Undergraduate
- Cross-Listed As:
- STAT0410A-S25
- Availability:
- View availability, prerequisites, and other requirements.
- Course Reference Number (CRN):
- 22519
- Subject Code:
- MATH
- Course Number:
- 0410
- Section Identifier:
- A