In this lecture, we mostly cover slides from Lecture G3 (on goodness of fit) that were missed during the previous lecture. In particular, we review hypothesis testing fundamentals (type-I error, type-II error, statistical power, sensitivity, false positive rate, true negative rate, receiver operating characteristic, ROC, alpha, beta) and then go into examples of using Chi-squared and Kolmogorov–Smirnov tests for goodness of fit for arbitrary distributions. We also introduce Anderson–Darling (for flexibility and higher power) and Shapiro–Wilk (for high-powered normality testing). We close with where we originally intended to start – with definitions of testing, verification, validation, and calibration. We will pick up from here next time.
Archived lectures from undergraduate course on stochastic simulation given at Arizona State University by Ted Pavlic
Tuesday, October 25, 2022
Lecture H (2022-10-25): Verification, Validation, and Calibration of Simulation Models (plus some Lecture G3 slides)
Subscribe to:
Post Comments (Atom)
Popular Posts
-
In this lecture, we go over course policies for the Fall 2022 session of IEE 475.
-
In this lecture, we wrap up the course content in IEE 475. We first do a quick overview of the four variance reduction techniques (VRT's...
-
In this lecture, we introduce the three different simulation methodologies (agent-based modeling, system dynamics modeling, and discrete eve...
-
This lecture section is a cumulative review of material from the semester and is meant to serve as a study guide for students preparing for ...
-
Today's lecture covers the basics of probability (including introduction to measure spaces) and random variables. We also go over some r...
-
In this lecture, we (nearly) finish our coverage of Input Modeling, where the focus of this lecture is on parameter estimation and assessing...
-
In this lecture, we continue to discuss hypothesis testing -- introducing parametric, non-parametric, exact, and non-exact tests and reviewi...
-
This lecture continues to discuss issues related to estimating absolute performance from transient and steady-state simulations (of terminat...
-
In this lecture, we review fundamentals of Discrete Event System (DES) simulation (e.g., entities, resources, activities, processes, delays,...
-
In this lecture, we introduce Industrial and Systems Engineering as a blend of science and engineering that necessitates model building. We ...
No comments:
Post a Comment