Ecological data analysis in R - 3 credits
Overview
This course is designed for beginners to teach the use of R for the analysis of ecological data. It will introduce students to several different analysis options for biological or ecological data (focusing specifically on community-level data) using the free & open-source statistical, mapping, and graphing platform R. Broad topics covered will include: introduction to R language and basic functions / graphics; basic mapping options; diversity measurement; univariate, multivariate, parametric and non-parametric analysis and their basis; functional diversity; and ecological time series analysis. Students will require a laptop for sessions. Schedule is subject to changes according to student progress.
This course is designed for beginners to teach the use of R for the analysis of ecological data. It will introduce students to several different analysis options for biological or ecological data (focusing specifically on community-level data) using the free & open-source statistical, mapping, and graphing platform R. Broad topics covered will include: introduction to R language and basic functions / graphics; basic mapping options; diversity measurement; univariate, multivariate, parametric and non-parametric analysis and their basis; functional diversity; and ecological time series analysis. Students will require a laptop for sessions. Schedule is subject to changes according to student progress.
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Objectives
Requirements
Evaluation (100%)
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Recommended literature
Borcard D, Gillet F, Legendre P (2011) Numerical ecology with R. Springer-Verlag New York, 306 p. DOI 10.1007/978-1-4419-7976-6
Paradis E (2002) R for Beginners, Institute des Sciences de l'Evolution University Montpellier II (2002), 72p. Available in resources
Zuur A, Ieno EN (2007) Analyzing ecological data. Springer-Verlag New York, 672 p. DOI 10.1007/978-0-387-45972-1
Borcard D, Gillet F, Legendre P (2011) Numerical ecology with R. Springer-Verlag New York, 306 p. DOI 10.1007/978-1-4419-7976-6
Paradis E (2002) R for Beginners, Institute des Sciences de l'Evolution University Montpellier II (2002), 72p. Available in resources
Zuur A, Ieno EN (2007) Analyzing ecological data. Springer-Verlag New York, 672 p. DOI 10.1007/978-0-387-45972-1
Content / schedule (subject to modification)
See links
See links
Course information & questions: vianney.denis(at)gmail(dot)com or R406, Institute of Oceanography, National Taiwan University