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Linear models

Course Description: A review of essential concepts in matrix algebra - Multivariate normal distribution - Quadratic forms and their distributions - The general linear model of full rank - Estimation and hypothesis testing for the full rank model - Estimation and hypothesis testing for the less than full rank model - Computational methods - Applications in the design of experiments and regression - Analysis of variance using statistical software.
Credit hours: 3
Prerequisites: MATH.242
Objectives of the course :

This course aims to delve into the use of linear models, utilizing multivariable linear analysis and statistical software.

Course outputs :

Acquiring knowledge on how to use linear modeling in experimental design, regression, and analysis of variance - acquiring cognitive skills in multiple linear analysis - acquiring practical skills in using statistical software in advanced statistics and data analysis.

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  • Last updated: 2026-06-04

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