Middlebury

MATH 0410

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.
Subject:
Mathematics
Department:
Mathematics & Statistics
Division:
Natural Sciences
Requirements Fulfilled:
DED
Equivalent Courses:

Sections in Spring 2011

Spring 2011

MATH0410A-S11 Lecture (Peterson)