Archived lectures from IEE 475 (Simulating Stochastic System) given by Ted Pavlic at Arizona State University. A course on discrete event system simulation focused on Industrial Engineering undergraduate students or others learning to use good simulation methodologies.
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Archived lectures from IEE 475 (Simulating Stochastic System) given by Ted Pavlic at Arizona State University. A course on discrete event system simulation focused on Industrial Engineering undergraduate students or others learning to use good simulation methodologies.
In this lecture, we review basic probability fundamentals (measure spaces, probability measures, random variables, probability density functions, probability mass functions, cumulative distribution functions, moments, mean/expected value/center of mass, standard deviation, variance), and then we start to build a vocabulary of different probabilistic models that are used in different modeling contexts. These include uniform, triangular, normal, exponential, Erlang-k, Weibull, and Poisson variables. We will finish the discussing next time with the Bernoulli-based discrete variables and Poisson processes.
IEE 475: Simulating Stochastic Systems
Archived lectures from IEE 475 (Simulating Stochastic System) given by Ted Pavlic at Arizona State University. A course on discrete event system simulation focused on Industrial Engineering undergraduate students or others learning to use good simulation methodologies.
