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IEMS 460-2 : (OPNS 516) Stochastic Processes II

Description

This course provides doctoral students the foundations of applied probability and stochastic modeling.  The first part of the course covers basic concepts in probability, such as the Borel Cantelli Lemma and the strong law of large numbers; the second part covers renewal and regenerative processes including Markov chains; and the last part covers Martingales and Brownian motion.  Throughout, we will be applying some of the theoretic results to the analysis of queues.  Students are expected to have some background in probability (such as IEMS 202) and stochastic processes; no measure theory background is required.