Apr 19, 2024  
Graduate Record 2020-2021 
    
Graduate Record 2020-2021 [ARCHIVED RECORD]

SYS 6005 - Stochastic Modeling I


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. Prerequisite: APMA 3100, 3120, or equivalent background in applied probability and statistics.



Credits: 3