Arizona State University IEE 475 Simulating Stochastic Systems
Professor Ted Pavlic · Arizona State University · 8 lectures with notes
Students in this class: ask your lecturer for the class code, and these lectures will already be in your library when you sign up.
IEE 475: Lecture F (2026-10-01): Midterm Review
Prepare for IEE 475 by mastering simulation concepts, inverse transforms, PRNG tests, and the two-stage midterm format.
IEE 475: Lecture E2 (2026-09-29): Random-Variate Generation
Test random-number quality, then transform uniform draws into exponential and triangular variates using inverse CDFs.
IEE 475: Lecture D2 (2026-09-22): Probabilistic Models
Choose simulation input distributions from what is known about the variable: its bounds, typical value, spread, or arrival process.
IEE 475: Lecture D1 (2026-09-17): Probability and Random Variables
A practical foundation in random variables, probability distributions, inverse-CDF sampling, and moments for simulation modeling.
IEE 475: Lecture C2 (2026-09-15): Beyond DES Simulation – SDM, ABM, and NetLogo
Choose DES, SDM, or ABM according to whether the question centers on process events, average trends, or spatial agent interactions.
IEE 475: Lecture C1 (2026-09-10): Basic Simulation Tools and Techniques
Monte Carlo simulation exposes system behavior and risk that steady-state averages and expected values can hide.
IEE 475: Lecture B3 (2026-09-08): Discrete-Event Simulation Examples, Part II
A spreadsheet can reproduce an M/M/1 simulation, while paired random schedules make policy comparisons less noisy.
IEE 475: Lecture B1 (2026-09-01): Fundamental Concepts of Discrete-Event Simulation
Discrete-event simulations advance from event to event, using process logic, resource constraints, and input distributions to model changing systems.