Middlebury

STAT 0211

Regression

Regression Theory and Applications (formerly MATH 0211)
Regression is a popular statistical technique for making predictions and for modeling relationships between variables. In this course we will discuss the theory and practical applications of linear, log-linear, and logistic regression models. Topics include least squares estimation, coding for categorical predictors, analysis of variance, and model diagnostics. We will apply these concepts to real datasets using R, a statistical programming language. (MATH 0200; and MATH 0116 or STAT 0116, or STAT 0201 or MATH 0311 or STAT 0311) (Not open to students who have taken ECON 0211) 3 hrs lect./disc.
Subject:
Statistics
Department:
Mathematics & Statistics
Division:
Natural Sciences
Requirements Fulfilled:
DED
Equivalent Courses:
MATH 0211

Sections

Fall 2024

STAT0211A-F24 Lecture (Malcolm-White)

Fall 2023

STAT0211A-F23 Lecture (Malcolm-White)