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.

Fitting General Linear Model: age based on leisure and edu
  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

From the table one can see that

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.

Fitting General Linear Model: age based on leisure and edu
  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

From the table one can see that

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.

Fitting General Linear Model: age based on leisure and edu
  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

From the table one can see that


This report was generated with R (3.0.1) and rapport (0.51) in 0.681 sec on x86_64-unknown-linux-gnu platform.