Rapport package team
 GLM
 2011-04-26 20:25 CET

Contents
•	Description
–	Introduction
•	Overview
–	Description
•	Introduction
•	Overview
–	Description
•	Introduction
•	Overview
Description
In this template Rapporter will present you GLM.
Introduction
Generalized Linear Model (GLM) is a generalization of the ordinary Linear Regression. While using GLM we don't need the assumption of normality for response variables. There are two basic ideas of the model: It allows the linear model to be related to the response variable via a link function and the magnitude of the variance of each measurement to be a function of its predicted value. An extinsion to the GLM is the Hierarchical generalized linear model.
Overview
Multivariate-General Linear Model was carried out, with Internet usage in leisure time (hours per day) and Internet usage for educational purposes (hours per day) as independent variables, and Age as a dependent variable. The interaction between the independent variables was taken into account.
 
	Estimate
	Std. Error
	z value
	Pr(>|z|)
	
(Intercept)
	3.198
	0.02122
	150.7
	0
	
leisure
	-0.02021
	0.005847
	-3.457
	0.000547
	
edu
	0.01474
	0.007586
	1.944
	0.05196
	
leisure:edu
	0.004439
	0.001795
	2.472
	0.01342
	
Fitting General Linear Model: age based on leisure and edu
From the table one can see that
•	(Intercept) has significant effect on the dependent variable, the p-value of that is 0
•	leisure has significant effect on the dependent variable, the p-value of that is 0.001
•	leisure:edu has significant effect on the dependent variable, the p-value of that is 0.013
Description
In this template Rapporter will present you GLM.
Introduction
Generalized Linear Model (GLM) is a generalization of the ordinary Linear Regression. While using GLM we don't need the assumption of normality for response variables. There are two basic ideas of the model: It allows the linear model to be related to the response variable via a link function and the magnitude of the variance of each measurement to be a function of its predicted value. An extinsion to the GLM is the Hierarchical generalized linear model.
Overview
Multivariate-General Linear Model was carried out, with Internet usage in leisure time (hours per day) and Internet usage for educational purposes (hours per day) as independent variables, and Age as a dependent variable. The interaction between the independent variables wasn't taken into account.
 
	Estimate
	Std. Error
	z value
	Pr(>|z|)
	
(Intercept)
	3.163
	0.01605
	197.1
	0
	
leisure
	-0.0095
	0.003888
	-2.443
	0.01455
	
edu
	0.03071
	0.003883
	7.91
	2.581e-15
	
Fitting General Linear Model: age based on leisure and edu
From the table one can see that
•	(Intercept) has significant effect on the dependent variable, the p-value of that is 0
•	leisure has significant effect on the dependent variable, the p-value of that is 0.015
•	edu has significant effect on the dependent variable, the p-value of that is 0
Description
In this template Rapporter will present you GLM.
Introduction
Generalized Linear Model (GLM) is a generalization of the ordinary Linear Regression. While using GLM we don't need the assumption of normality for response variables. There are two basic ideas of the model: It allows the linear model to be related to the response variable via a link function and the magnitude of the variance of each measurement to be a function of its predicted value. An extinsion to the GLM is the Hierarchical generalized linear model.
Overview
Multivariate-General Linear Model was carried out, with Internet usage in leisure time (hours per day) and Internet usage for educational purposes (hours per day) as independent variables, and Age as a dependent variable. The interaction between the independent variables wasn't taken into account.
 
	Estimate
	Std. Error
	t value
	Pr(>|t|)
	
(Intercept)
	0.0422
	0.0008599
	49.08
	4.612e-212
	
leisure
	0.0003828
	0.0002093
	1.829
	0.06785
	
edu
	-0.001182
	0.0001948
	-6.065
	2.332e-09
	
Fitting General Linear Model: age based on leisure and edu
From the table one can see that
•	(Intercept) has significant effect on the dependent variable, the p-value of that is 0
•	edu has significant effect on the dependent variable, the p-value of that is 0
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This report was generated with R (3.0.1) and rapport (0.51) in 0.681 sec on x86_64-unknown-linux-gnu platform.