Description

This course will introduce the Bayesian approach to statistical modeling as well as the computational methods necessary to implement these approaches in research and applications. We will cover methods of statistical learning and inference for a variety of subject area. Students will have the opportunity to apply these concepts and methods in the context of their own research or area of application in the form of a term project.

Prerequisites

ENGS 93 or comparable course in probability and statistics; previous programming experience with Matlab, C, S, R or similar language. (MATH/COSC 71, ENGS 91, COSC 70/170 are appropriate ways to fulfill the programming requirement.) We will use R language code.

Notes

This course will be offered as ENGS 107 after the 2023-2024 academic year.