Getting Started with R An Introduction for Biologists

by Beckerman, Andrew P.; Petchey, Owen L.

• ISBN13: 9780199601615
• ISBN10: 0199601615
• Format: Hardcover
• Copyright: 2012-07-22
• Publisher: Oxford University Press

Summary

Learning how to get answers from data is an integral part of modern training in the natural, physical, social, and engineering sciences. One of the most exciting changes in data management and analysis during the last decade has been the growth of open source software. The open source statistics and programming language R has emerged as a critical component of any researcher's toolbox. Indeed, R is rapidly becoming the standard software for analyses, graphical presentations, and programming in the biological sciences. This book provides a functional introduction for biologists new to R. While teaching how to import, explore, graph, and analyse data, it keeps readers focused on their ultimate goals - communicating their data in oral presentations, posters, papers, and reports. It also provides a consistent method (workflow) for using R that is simple, efficient, reliable, accurate, and reproducible. The material in the book reproduces the engaging and sometimes humorous nature of the three-day course on which it is based.

Table of Contents

Preface	p. vii
What this book is about	p. vii
What you need to know to make this book work for you	p. viii
How the book is organized	p. ix
Why R?	p. 1
Import, Explore, Graph I-Getting Started	p. 5
Where to put your data	p. 7
Make a folder for your instructions (code, script)	p. 10
How to get your data into R and where it is stored in R's brain	p. 10
Working with R-hints for a successful first (and more) interaction	p. 11
Make your first script file	p. 15
Starting to control R	p. 18
Making R work for you-developing a workflow	p. 19
And finally…	p. 21
Import, Explore, Graph II-Importing and Exploring	p. 23
Getting your data into R	p. 23
Checking that your data is your data	p. 26
Summarizing your data-quick version	p. 28
How to isolate, find, and grab parts of your data-I	p. 28
How to isolate, find, and grab parts of your data-II	p. 30
Aggregation and how to use a help file	p. 31
What your first script might look like (what you should now know)	p. 35
Import, Explore, Graph III-Graphs	p. 39
The first step in data analysis-making a picture	p. 39
Making a picture-bar graphs	p. 40
Pimp my barplot	p. 44
Making a picture-scatterplots	p. 50
Pimp my scatterplot: axis labels	p. 53
Pimp my scatterplot: points	p. 54
Pimp my scatterplot: colours (and groups)	p. 56
Pimp my scatterplot: legend	p. 59
Plotting extras: pdfs, layout, and the lattice package	p. 64
Doing your Statistic in R-Getting Started	p. 65
Chi-square	p. 66
Two sample t-test	p. 70
The first step: plot your data	p. 72
The two sample t-test analysis	p. 76
General linear models	p. 77
Always start with a picture	p. 78
Potential statistical and biological hypotheses-it's all about lines	p. 80
Specifying the model	p. 83
Plot, model, then assumptions	p. 84
Interpretation	p. 86
Treatment contrasts and coefficients	p. 89
Interpretation	p. 89
Making a publication quality figure	p. 92
Coefficients, lines, and lines()	p. 93
Expanded grids, prediction, and a more generic model plotting method	p. 94
The final picture	p. 99
An analysis workflow	p. 101
Final Comments and Encouragement	p. 105
Appendix: References and Datasets	p. 109
Index	p. 111
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