# 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
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Offered as Cross-Listing Only
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| Spring | Summer | Fall
--- | --- | --- | ---
| (Session 1) | (Session 2) |

2026

Stochastic Processes And Modeling (4c)

- Fabian Maximilian Faulstich

Seats Taken: 22/25

2025 |  |  |

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

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