STA 264 - (MTH 264) Regression Analysis

Course Units: 1

Regression analysis is one of the most important and influential methods in statistics, finding application in virtually all disciplines, from business to healthcare to sociology to the hard sciences. This course will cover both the science of regression analysis - its underlying mathematical theory, as well as the art of its practical application. The course project will involve development of a regression model to fit a real data set. Lectures will be given primarily in matrix notation, i.e., using linear algebra. While the course will not be all-encompassing in itself due to time constraints, it would be good preparation for more advanced modeling courses involving data mining, machine learning, “Big Data”, and so on. Prior understanding of statistical concepts is assumed Prerequisite(s): MTH 115 and STA 104 (MTH-104), ECO 243, STA 164 (MTH 164), PSY 200, MER 301 or permission from the Chair, which may be granted to upper class students who have solid backgrounds in calculus and linear algebra, e.g., who have taken MTH 115 .