Course description

A rigorous foundation in theory combined with the methods for modeling, analyzing, and controlling randomness in engineering problems. Probabilistic ideas are used to construct models for engineering problems, and statistical methods are used to test and estimate parameters for these models. Specific topics include random variables, probability distributions, density functions, expectation and variance, multidimensional random variables, and important distributions including normal, Poisson, exponential, hypothesis testing, confidence intervals, and point estimation using maximum likelihood and the method of moments.

Prerequisites

ENGRD 2700 or equivalent.

No upcoming classes were found.

Previously offered classes

Summer 2024: Online course

Marie Chazal
Marie Chazal
Visiting Lecturer, Operations Research and Information Engineering

Summer 2024: Online course

Marie Chazal
Marie Chazal
Visiting Lecturer, Operations Research and Information Engineering