COURSE SYLLABUS

Ohio Northern University

College of Arts and Sciences

Department of Mathematics

Effective Date: Winter 2005-06

Course: STAT 281 Name: Applied Regression

Credit hours: 4 Lecture hours/week: 4 Lab hours/week: 0

Instructor: Robinson or staff

Usual student level: Sophomores, Juniors, and Seniors

Course required of students in: Math/Stat major

Course frequency per year: Once each or every other year

Average enrollment per year: 8

This course has a prerequisite: STAT 156, 256, or 280; STAT 142 or 146 with instructor permission

This course is a prerequisite for: Statistical computing

Catalog Description: Linear and multiple regression with applications.

Course Objectives: To develop a fundamental understanding of the concepts of applied regression analysis

Textbook (recommended): A cheap copy of one of the editions of “Applied Linear Statistical Models” by Neter et al. (Irwin)

NOTE: TI-83 or TI-86 required

Outline of content follows: (see attached)

Course Outline

STAT 281

Title: Applied Regression

Simple linear regression and correlation

Least squares estimation

Inferences for regression parameters

Prediction intervals

Analysis of variance table for regression analysis

Coefficients of determination and correlation

Regression through the origin

Relation between simple regression, single-factor ANOVA, and the two-sample

problem with regard to a single dichotomous predictor variable

Multiple regression

Polynomial regression

Models with interaction

Least squares estimation, inferences for regression parameters, ANOVA

table for regression analysis, coefficients of multiple determination and

correlation

Partial correlation

Joint confidence regions

Issues of confounding

Issues of precision

Analysis of covariance

Models with dichotomous response

Study design

Experimental vs. observational designs

Completely randomized vs. randomized block experimental designs

Matched vs. unmatched data