Chapter 2
Exploratory Data Analysis
2.1 Objectives
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;
• orient further analyses.
As a worked example, we will explore the classical Doubs River dataset to
introduce some techniques of EDA using R functions found in standard packages.
In this chapter you will:
• learn or revise some bases of the R language;
• learn some EDA techniques applied to multidimensional ecological data;
• explore the Doubs dataset in hydrobiology as a first worked example.
2.2 Data Exploration
2.2.1 Data Extraction
The Doubs data used here are available in a .RData file found among the files
provided with the book; see Chap. 1.
© Springer International Publishing AG, part of Springer Nature 2018
D. Borcard et al., Numerical Ecology with R, Use R!,
https://doi.org/10.1007/978-3-319-71404-2_2
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