Spring 2026 Statistics GR5205 section 002

LINEAR REGRESSION MODELS

Call Number 20135
Day & Time
Location
MW 6:10pm-7:25pm
517 Hamilton Hall
Points 3
Grading Mode Standard
Approvals Required None
Instructor Gabriel Young
Type LECTURE
Method of Instruction In-Person
Course Description

Prerequisites: STAT GR5203 and GR5204 or the equivalent. Theory and practice of regression analysis, Simple and multiple regression, including testing, estimation, and confidence procedures, modeling, regression diagnostics and plots, polynomial regression, colinearity and confounding, model selection, geometry of least squares. Extensive use of the computer to analyse data.

Web Site Vergil
Department Statistics
Enrollment 10 students (55 max) as of 11:07AM Tuesday, January 20, 2026
Subject Statistics
Number GR5205
Section 002
Division Interfaculty
Open To GSAS
Note Open to MA in Statistics Students, MAFN Students, and DSI St
Section key 20261STAT5205W002