In this lecture, we revisit some basics of hypothesis testing and then go on to introduce verification, validation, and calibration in the context of simulation models. This will ultimately move us away from goodness-of-fit tests of input models toward hypothesis tests of output performance (e.g., to detect differences from different simulations scenarios and confirm that simulations of real-world scenarios match our expectations from real-world data).
Archived lectures from undergraduate course on stochastic simulation given at Arizona State University by Ted Pavlic
Wednesday, October 28, 2020
Lecture H (2020-10-27): Verification, Validation, and Calibration of Simulation Models
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