![IEE 475: Simulating Stochastic Systems artwork](https://is4-ssl.mzstatic.com/image/thumb/Features/v4/5f/88/96/5f8896e9-9be5-529a-af14-cc807367568a/mza_1382744875394257421.png/100x100bb.jpg)
Lecture D1 (2022-09-15): Probability and Random Variables
IEE 475: Simulating Stochastic Systems
English - September 15, 2022 23:05Courses Education simulation stochastic des dess discrete event system industrial engineering modeling Homepage Download Apple Podcasts Google Podcasts Overcast Castro Pocket Casts RSS feed
Previous Episode: Lecture C2 (2022-09-13): Beyond DES Simulation – SDM, ABM, and NetLogo (and pre-lab discussion for Lab 4 and post-lab discussion for Lab 3)
Next Episode: Lecture D2 (2022-09-20): Probabilistic Models
In this lecture, we introduce the measure-theoretic concept of a random variable (which is neither random nor a variable) and related terms, such as outcomes, events, probability measures, moments, means, etc. Throughout the lecture, we use the metaphor of probability as mass (and thus probability density as mass density, and a mean as a center of mass). This allows us to discuss the "statistical leverage" of outliers in a distribution (i.e., although they happen infrequently, they still have the ability to shift the mean significantly, as in physical leverage). This sets us up to talk about random processes and particular random variables in the next lecture.