Covers basic stochastic processes with emphasis on model building and probabilistic reasoning. The approach is non-measure theoretic but otherwise rigorous. Topics include a review of elementary probability theory with particular attention to conditional expectations; Markov chains; optimal stopping; renewal theory and the Poisson process; martingales. Applications are considered in reliability theory, inventory theory, and queuing systems.
Stochastic Modeling I
Host University
University of Virginia
Semester
Fall 2022
Course Number
SYS 6005
Discipline
Systems Engineering, Operations Research and Engineering Management
Instructor
Tariq Iqbal
Course Information
Prerequisites
APMA 3100, 3120, or equivalent background in applied probability and statistics