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Course Description
Stochastic Foundations (OPNS-483-1)
Variable Credit
Description:
This course counts toward the following majors: Operations. 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.
Prerequisites:
None
Corequisites:
None
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