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Introduction to Linear Regression

Introduction to Linear Regression
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Copyright: 2017
Pages: 8
Source title: Comparative Approaches to Using R and Python for Statistical Data Analysis
Source Author(s)/Editor(s): Rui Sarmento (University of Porto, Portugal)and Vera Costa (University of Porto, Portugal)
DOI: 10.4018/978-1-68318-016-6.ch006

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Abstract

In statistical modelling, regression analysis is a statistical process for estimating the relationships among variables. More specifically, regression analysis helps the reader understand how the dependent variable changes when any of the independent variables is varied. Thus, regression analysis estimates the average value of the dependent variable when the independent variables are fixed. Therefore, the estimation target is a function of the independent variables called regression function. In limited circumstances, regression analysis can be used to infer causal relationships between the independent and dependent variables. Nonetheless, caution has to be taken since correlation might not signify causality. Regression analysis techniques are varied. Nevertheless, in this chapter, we will present only the fundamental analysis.

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