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Exploratory Data Analysis

  • Daniel Borcard
  • François Gillet
  • Pierre Legendre
Chapter
Part of the Use R! book series (USE R)

Abstract

Nowadays, most ecological research is done with hypothesis testing and modelling in mind. However, Exploratory Data Analysis (EDA), with its visualization tools and simple statistics, is still required at the beginning of the statistical analysis of multidimensional data, in order to get an overview of the data, transform or recode some variables or orient further analyses. In this chapter you will learn or revise some bases of the R language, learn some EDA techniques that are frequently applied to multidimensional ecological data and explore the Doubs dataset in hydrobiology as a first worked example, using R functions mostly found in standard packages.

Bibliography

  1. Anderson, M.J., Ellingsen, K.E., McArdle, B.H.: Multivariate dispersion as a measure of beta diversity. Ecol. Lett. 9, 683–693 (2006)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Daniel Borcard
    • 1
  • François Gillet
    • 2
  • Pierre Legendre
    • 1
  1. 1.Département de sciences biologiquesUniversité de MontréalMontréalCanada
  2. 2.UMR Chrono-environnementUniversité Bourgogne Franche-ComtéBesançonFrance

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