Getting Started with R: An Introduction for Biologists

R is rapidly becoming the standard software for statistical analyses, graphical presentation of data, and programming in the natural, physical, social, and engineering sciences. Getting Started with R is now the go-to introductory guide for biologists wanting to learn how to use R in their research. It teaches readers how to import, explore, graph, and analyse data, while keeping them focused on their ultimate goals: clearly communicating their data in oral presentations, posters, papers, and reports. It provides a consistent workflow for using R that is simple, efficient, reliable, and reproducible.

This second edition has been updated and expanded while retaining the concise and engaging nature of its predecessor, offering an accessible and fun introduction to the packages dplyr and ggplot2 for data manipulation and graphing. It expands the set of basic statistics considered in the first edition to include new examples of a simple regression, a one-way and a two-way ANOVA. Finally, it introduces a new chapter on the generalised linear model.

Getting Started with R is suitable for undergraduates, graduate students, professional researchers, and practitioners in the biological sciences.

Author: Andrew P. Beckerman, Dylan Z. Childs, Owen L. Petchey
Publisher: Oxford University Press, USA
Published: 03/26/2017
Pages: 256
Binding Type: Paperback
Weight: 1.10lbs
Size: 6.60h x 9.40w x 0.60d
ISBN: 9780198787846

About the Author
Andrew Beckerman, Department of Animal and Plant Science, University of Sheffield, Owen Petchey, Department of Evolutionary Biology and Environmental Studies, University of Zurich, Dylan Childs, Department of Animal and Plant Science, University of Sheffield

Andrew leads a research team studying community and evolutionary ecology. He has been using R and teaching quantitative methods for over 16 years.

Owen leads a research team studying ecological forecasting. He has been using R and teaching quantitative methods for over 16 years.

Dylan leads a research team studying population biology. He has been using R and teaching quantitative methods for over 15 years.