STAT 4120

Applied Linear Models

Course Description

Prerequisites

A prior course in statistics and a prior course in linear algebra

Disciplines

Quantification, Computation & Data Analysis

This course includes linear regression models, inferences in regression analysis, model validation, selection of independent variables, multicollinearity, influential observations, and other topics. Conceptual discussion is supplemented with hands-on practice in applied data-analysis tasks. Highly recommended: A prior course in applied regression such as STAT 3220.

Instructors

Current All Time

Jeffrey Woo