# 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:
MATH-2400 Intro Diff Equations

# Past Term Data
Offered
Not Offered
Offered as Cross-Listing Only
No Term Data
Simple View
Detailed View

| Spring | Summer | Fall
--- | --- | --- | ---
| (Session 1) | (Session 2) |
2025 | Stochastic Processes And Modeling (4c) Peter R Kramer Seats Taken: 0/20 |  |
2024 | Stochastic Processes And Modeling (4c) Peter R Kramer Seats Taken: 3/20 |  |
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 |  |  |
2006 |  |  |
2005 |  |  |
2004 |  |  |
2003 |  |  |
2002 |  |  |
2001 |  |  |
2000 |  |  |
1999 |  |  |
1998 |  |  |