MATH 620 Stochastic Processes
This course will introduce the definitions, theories and applications of different stochastic processes. Topics include Markov chains, Poisson processes, renewal processes, continuous time Markov chains and Martingales.
Prerequisites: Bachelor's degree in mathematics, mathematics education, statistics or related field. Note: Graduate admission status required. Students whose prerequisites are not identified by the system should contact the Math and Statistics Department for an override at MATH@metrostate.edu.
18 Credit Credentialing Pathways
Special information
18 Credit Credentialing Pathways
3 Graduate credits
Effective August 19, 2018 to present
Learning outcomes
General
- Understand the stochastic processes in the areas of biology, ecology, finance and engineering
- Calculate probabilities related to the stochastic processes
- Construct stochastic models using the stochastic processes