Presenting Scientific Data in R: Creating effective graphs and figures (Oxford Biology Primers)

Written primarily for students embarking on an undergraduate bioscience degree, this primer provides an accessible, straightforward, and approachable guide to data presentation using R. It offers valuable and widely applicable advice on how to choose the most appropriate type of graph for different types of data, and guides readers from the basics of plotting clear figures to producing polished and effective visuals, illustrating the core concepts and features of excellent graphing. This primer uses simple and engaging biology-based example data sets to take readers from the essential aspects of basic plots to more advanced graphing techniques and details. Digital formats and resources The book is available for students and institutions to purchase in a variety of formats, and is supported by online resources: - The e-book offers a mobile experience and convenient access along with functionality tools, navigation features, and links that offer extra learning support: www.oxfordtextbooks.co.uk/ebooks - Online resources include extended supplementary resources to guide use of R, multiple choice questions for students to check their understanding, and, for registered adopters, figures and tables from the book

Rosalind Humphreys is a researcher at the University of St Andrews. Rosalind's research focuses on the behavioural and evolutionary ecology of interactions between species, but she has published peer-reviewed papers on statistical topics as well as reviews and original research articles concerning predator-prey interactions. Rosalind also acted as sole graphics designer for the Oxford Biology Primer Power Analysis: An Introduction for the Life Sciences by Colegrave and Ruxton (2020). Graeme Ruxton is Professor of Evolutionary Ecology at the University of St Andrews. Graeme has co-authored (with Nick Colegrave) four editions of the OUP textbook Experimental Design for the Life Sciences. With a long history of publishing papers aimed at improving the design and analysis of experiments, Graeme has a particular interest in making the principles of data analysis readily accessible to a wide range of learners.