STAT 551 Applied Random Processes

Introduction to random processes, also called stochastic processes. Topics may include conditional probability, random variables, theory and simulation of finite Markov chains, Gibbs sampler, Metropolis-Hastings algorithm, theory and simulation of Poisson processes. Use of computer software such as R or Python.