Introduction to Linear Models
Prepared by:
Dejen Tesfaw (PhD)
Email:
[email protected]
Tel: 0935316506
Addis Ababa University
College of Natural & Computational
Sciences
Department of Statistics
1

** Subscribe** to view the full document.

•
The concept & types of classical linear models
The multiple linear regression models
The Analysis of variance (ANOVA) models
The analysis of covariance (ANCOVA) models
Learning Objectives
After studying this chapter
students’ should
be able to understand:
2

1) Introduction to Linear Models
Classical linear models:
The core of the field of statistics,
and are probably the most commonly used set of
statistical techniques in practice.
Some of the main classes of the classical linear models
are:
1. Linear regression models:
Simple linear regression (one response, one predictor)
Multiple linear regression (multiple regression is not the same
as multivariate regression)
Multiple regression:- only one response variable (dependent variable)
and several predictors (regressors, independent variables)
Multivariate regression:- more than one response variable and
predictors could be one or more.
3

** Subscribe** to view the full document.