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Apr 30, 2024
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STAT 753 - Stochastic Models and Simulation (3 units)
Stochastic process models with applications. Analytic and computer modeling techniques for Markov chains, Poisson processes, Markov processes, Empirical processes, Brownian motion, and special topics.
Prerequisite(s): MATH 330 ; STAT 461 or STAT 661 .
Grading Basis: Graded
Units of Lecture: 3
Offered: Every Spring
Student Learning Outcomes
Upon completion of this course, students will be able to:
1. demonstrate understanding of the probability foundations of various stochastic process models through proofs, examples, and computer simulations.
2. use appropriate stochastic processes to model various scientific phenomena.
3. use analytic and numerical techniques to analyze essential stochastic processes, including Markov chains, Poisson processes, Markov processes, and Brownian motion.
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