Lecture D2 (2025-09-23): Probabilistic Models

from IEE 475: Simulating Stochastic Systems Hosted by Theodore P. Pavlic

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.

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Lecture D2 (2025-09-23): Probabilistic Models

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This episode was published on September 23, 2025.

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