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Introduction to Linear Regression

Introduction to Linear Regression

Copyright: © 2017 |Pages: 8
ISBN13: 9781683180166|ISBN10: 168318016X|EISBN13: 9781522519898
DOI: 10.4018/978-1-68318-016-6.ch006
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MLA

Rui Sarmento and Vera Costa. "Introduction to Linear Regression." Comparative Approaches to Using R and Python for Statistical Data Analysis, IGI Global, 2017, pp.140-147. https://doi.org/10.4018/978-1-68318-016-6.ch006

APA

R. Sarmento & V. Costa (2017). Introduction to Linear Regression. IGI Global. https://doi.org/10.4018/978-1-68318-016-6.ch006

Chicago

Rui Sarmento and Vera Costa. "Introduction to Linear Regression." In Comparative Approaches to Using R and Python for Statistical Data Analysis. Hershey, PA: IGI Global, 2017. https://doi.org/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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