Presenting Scientific Data in R
Creating effective graphs and figures
Published on 25. July 2022
Book
Paperback/Softback
208 pages
978-0-19-887047-0 (ISBN)
Description
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
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
More details
Series
Language
English
Place of publication
Oxford
United Kingdom
Target group
College/higher education
Dimensions
Height: 190 mm
Width: 245 mm
Thickness: 12 mm
Weight
412 gr
ISBN-13
978-0-19-887047-0 (9780198870470)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
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.
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.
Content
- 1: Introduction and getting started
- 2: Pie charts and tables for qualitative data
- 3: Bar charts for qualitative data
- 4: Presenting single-sample data: Histograms and boxplots
- 5: Comparing multiple samples: Boxplots and histograms
- 6: Scatterplots for quantitative data
- 7: Customizing everything using R: Day-to-day
- 8: Customizing everything using R: More specialist