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
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•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