Stochastic Processes and Modeling

MATH-6660

This course provides an introduction to methods and concepts to model and analyze the dynamics of system with uncertain inputs or too many variables to track explicitly. Topics may include Markov processes, point processes, renewal processes, and/or stochastic differential equations. Applications will be developed and illustrated on examples drawn from physics, biology, chemistry, industry, and finance.

4 credits
Prereqs:
none

Past Term Data

Offered
Not Offered
Offered as Cross-Listing Only
No Term Data
Spring Summer Fall
(Session 1) (Session 2)
2023
2022
Stochastic Proc. And Modeling (4c)
  • Peter R Kramer
Seats Taken: 9/30
2021
2020
2019
Stochastic Processes And Modeling (4c)
  • Peter R Kramer
Seats Taken: 11/30
2018
Stochastic Processes And Modeling (4c)
  • Peter R Kramer
Seats Taken: 17/30
2017
2016
2015
Stochastic Processes And Modeling (4c)
  • Peter R Kramer
Seats Taken: 24/30
2014
Stochastic Processes And Modeling (4c)
  • Peter R Kramer
Seats Taken: 24/30
2013
2012
2011
2010
2009
2008
2007