The R Software pp 455-501 | Cite as

Simple and Multiple Linear Regression

  • Pierre Lafaye de Micheaux
  • Rémy Drouilhet
  • Benoit Liquet
Part of the Statistics and Computing book series (SCO, volume 40)


This chapter is a brief introduction to simple and multiple linear regression and how to use this method in a real context (see [41] for a more complete presentation). We present the relevant R commands and use a real data set as a connecting thread as we present the key concepts for this method. We treat the case of qualitative explanatory variables, as well as interaction of explanatory variables. We discuss model validation with a study of residuals and mention the issue of collinearity. We also present a few methods for variable selection.


Explanatory Variable Linear Regression Model Variance Inflation Factor Simple Linear Regression Prediction Interval 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Pierre Lafaye de Micheaux
    • 1
  • Rémy Drouilhet
    • 2
  • Benoit Liquet
    • 3
  1. 1.Department of Mathematics and StatisticsUniversité de MontréalMontréalCanada
  2. 2.B.S.H.MGrenobleFrance
  3. 3.School of Mathematics and PhysicsThe University of QueenslandBrisbaneAustralia

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