Overview
Description
Stochastic process models with applications. Analytic and computer modeling techniques for Markov chains, Poisson processes, Markov processes, Empirical processes, Brownian motion, and special topics.
Requirements
Prerequisites
MATH 330STAT 461STAT 661
Original catalog text
Prerequisites
Prerequisite(s): MATH 330; STAT 461 or STAT 661.
Units
Lecture3
Catalog Details
Offering
Offered: Every Spring
Terms
spring
Attributes
Standard
Learning Outcomes
- demonstrate understanding of the probability foundations of various stochastic process models through proofs, examples, and computer simulations.
- use appropriate stochastic processes to model various scientific phenomena.
- use analytic and numerical techniques to analyze essential stochastic processes, including Markov chains, Poisson processes, Markov processes, and Brownian motion.