Stochastic Models

IE 325 is where probability stops being about coin flips and starts being a language for modeling systems that evolve randomly over time — machines that fail, queues that build up, inventories that drain. You'll spend the semester setting up Markov chains and Poisson processes for concrete scenarios, then computing long-run probabilities, expected costs, and steady-state behavior through homeworks, quizzes, and two midterms. It's the bridge between your earlier probability course and the operations-research electives (queueing, simulation, supply chain) that assume you can already think in transition matrices and rate diagrams.