Course Outline – MATH 4430A – Stochastic Processes

MATH 4430 3.0AF (Fall 2020)

Stochastic Processes – Course Outline

  • Description: This course begins by reviewing conditional expectations and other key topics from probability theory. We then discuss counting processes and discrete time Markov chains. We consider the classification of states, first step analysis, invariant measures, and first passage times, as well as applications in science and business. Moving to continuous time, we consider diffusion processes and Brownian motion. We will treat both analytical results and stochastic simulation, the latter using the R programming language. This course is integrated with MATH 6602

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