STAT 433 - Stochastic Modeling

4 Credit(s)

This is a course in stochastic processes with emphasis on model building and probabilistic reasoning. Topics to be covered may include a review of elementary probability theory, Poisson processes, discrete and continuous time Markov chains, Brownian motion, random walks, and martingales. Applications will be drawn from the physical, biological, and social sciences. Students will learn hands-on design and construction of working models using appropriate technology. Upon successful completion of this course, the student should be proficient in asking research questions, collecting and arranging data, and designing models to answer the questions asked.

Prerequisite(s): STAT 121 and M 210 grade B- or higher; or c/i.
(spring/even-numbered years)