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MATH 620

Stochastic Processes

3 Graduate credits
Effective August 19, 2018 – Present

Graduation requirements this course fulfills

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.

Special information

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

Learning outcomes


  • 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

Fall 2020

Section Title Instructor
01 Stochastic Processes Calcaterra, Craig Books Course details