STAT 478 - Regression Analysis

Simple and multiple linear regression theory and applications, including matrix formulation, estimation and inference, validation of assumptions, model building, time series and one-way ANOVA as regression models, and logistic regression.

Credit(s): 3
Prerequisite(s): (STAT 330 - Introduction to Linear Models or STAT 331 - Biostatistics or STAT 375 - ANOVA/Experimental Design or STAT 378 - Linear Regression/Time Series) AND (MATH 192 - Essentials of Calculus or MATH 198 - Analytic Geometry and Calculus I), AND (MATH 285 - Matrix Algebra or MATH 357 - Linear Algebra), AND STAT 250 - Statistical Computing.
Disciplinary Perspective(s):
None
Interconnecting Perspective(s):
None
University Graduation Requirement(s):
Honors Scholar