School navigation

Mathematical Sciences

Fall Term 2013
Taught by Yung-Pin Chen
MWF 10:20 - 11:20 am

This course introduces linear regression analysis that is widely employed to model the relationship between a response variable and a set of candidate explanatory variables. It aims to blend both theory and application so that students will gain an understanding of the fundamental concepts and methods for applying regression model-building techniques in a wide variety of disciplines. Matrix algebra will be
used to establish a general theoretic framework for presenting regression models and drawing statistical inference. Real-world data will be used to illustrate the basic regression analysis principles.

[The statistical software R will be used in the course.]

Prerequisites: Linear algebra; a statistical course equivalent to or beyond Math 255; some experience in a programming language.