Listed in: Mathematics and Statistics, as MATH-365
Tanya L. Leise (Section 01)
A stochastic process is a collection of random variables used to model the evolution of a system over time. Unlike deterministic systems, stochastic processes involve an element of randomness or uncertainty. Examples include stock market fluctuations, audio signals, EEG recordings, and random movement such as Brownian motion and random walks. Topics will include Markov chains, martingales, Brownian motion, and stochastic integration, including Ito’s formula. Four class hours per week, with weekly in-class computer labs.
Requisite: MATH 360 or consent of instructor. Limited to 24 students. Spring semester. Professor Leise.
If Overenrolled: Preference will be given to math majors and then to juniors and seniors.
Cost: $93 ?
Section 01
M 09:00 AM - 09:50 AM SMUD 205
W 09:00 AM - 09:50 AM SMUD 205
F 09:00 AM - 09:50 AM SMUD 205
Section 01
Th 09:00 AM - 09:50 AM SMUD 205
| ISBN | Title | Publisher | Author(s) | Comment | Book Store | Price |
|---|---|---|---|---|---|---|
| Introduction to Stochastic Processes with R | Wiley 2016 | Dobrow | Available free as Ebook through Five Colleges library catalog | TBD |