Prerequisites
Math 227 and Math 325 with a grade C or better.Bulletin Description
Theory and application of linear models. The topics covered are multiple linear regression, analysis of variance for fixed and random effects and nested and crossed treatments, and experimental design, especially factorial designs.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
| Topics |
| 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 ModelsSubmitted by: M. R. Kafai
Date: Feb 9th, 2006
