MATH 424: Introduction to Linear Models

Prerequisites & Bulletin Description

Course Objectives

Students will gain an understanding of the linear model and gain practical experience applying linear model to analyze real-life data. The course objective are:

  • Understand the statistical foundation of the linear model including major distributions. 
  • Understand how to interpret the results of regression analysis. 
  • Assessing the quality of the regression model. 
  • Understand how to set the model structure in analysis of variance. 

Evaluation of Students

Student will evaluated based on homework, projects, midterm and final examinations.

Course Outline


  • Introduction to Linear Models
  • Transformations
  • Inference in Linear Regression
  • Regression Diagnostics
  • Regression in Matrix Notation
  • Multiple Regression
  • Qualitative Predictor Variables
  • Model Building Strategies
  • Single Factor Analysis of Variance
  • Analysis of Covariance
  • Two Factor Analysis of Variance

Textbooks & Software

Neter, Kutner, Nachtsheim and Wasserman, Applied Linear Statistical Models

Submitted by: M. R. Kafai 
Date: February 9, 2006