IE 575LEC - Stochastic Methods

This course teaches the fundamentals of applied probability theory. Topics include algebra of events; sample space representation of the model of an experiment (any non-deterministic process); random variables; derived probability distributions; discrete and continuous transforms and random incidence. The course also introduces elementary stochastic processes including Bernoulli and Poisson processes and general discrete-state Markov processes. This is followed by a discussion of some basic limit theorems and some common issues and techniques of both classical and Bayesian statistics.

Credits: 3