Getting started with R : an introduction for biologists / Andrew P. Beckerman & Owen L. Petchey.

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"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 an...

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Bibliographic Details
Main Author: Beckerman, Andrew P.
Other Authors: Petchey, Owen L.
Language:English
Published: Oxford : Oxford University Press, 2012.
Edition:First edition.
Subjects:
R (Computer program language)
Biology > Software.
Biology > Data processing.
Genre:
Software.
Physical Description:x, 113 pages : illustrations (some color) ; 25 cm
Format: Book
Contents:
  • Chapter 1 Why R? 1
  • Chapter 2 Import, Explore, Graph I-Getting Started 5
  • 2.1 Where to put your data 7
  • 2.2 Make a folder for your instructions (code, script) 10
  • 2.3 How to get your data into R and where it is stored in R's brain 10
  • 2.4 Working with R-hints for a successful first (and more) interaction 11
  • 2.5 Make your first script file 15
  • 2.6 Starting to control R 18
  • 2.7 Making R work for you-developing a workflow 19
  • 2.8 And finally ... 21
  • Chapter 3 Import, Explore, Graph II-Importing and Exploring 23
  • 3.1 Getting your data into R 23
  • 3.2 Checking that your data is your data 26
  • 3.3 Summarizing your data-quick version 28
  • 3.4 How to isolate, find, and grab parts of your data-I 28
  • 3.5 How to isolate, find, and grab parts of your data-II 30
  • 3.6 Aggregation and how to use a help file 31
  • 3.7 What your first script might look like (what you should now know) 35
  • Chapter 4 Import, Explore, Graph III-Graphs 39
  • 4.1 The first step in data analysis-making a picture 39
  • 4.2 Making a picture-bar graphs 40
  • 4.2.1 Pimp my barplot 44
  • 4.3 Making a picture-scatterplots 50
  • 4.3.1 Pimp my scatterplot: axis labels 53
  • 4.3.2 Pimp my scatterplot: points 54
  • 4.3.3 Pimp my scatterplot: colours (and groups) 56
  • 4.3.4 Pimp my scatterplot: legend 59
  • 4.4 Plotting extras: pdfs, layout, and the lattice package 64
  • Chapter 5 Doing your Statistics in R-Getting Started 65
  • 5.1 Chi-square 66
  • 5.2 Two sample t-test 70
  • 5.2.1 The first step: plot your data 72
  • 5.2.2 The two sample t-test analysis 76
  • 5.3 General linear models 77
  • 5.3.1 Always start with a picture 78
  • 5.3.2 Potential statistical and biological hypotheses-it's all about lines 80
  • 5.3.3 Specifying the model 83
  • 5.3.4 Plot, model, then assumptions 84
  • 5.3.5 Interpretation 86
  • 5.3.6 Treatment contrasts and coefficients 89
  • 5.3.7 Interpretation 89
  • 5.4 Making a publication quality figure 92
  • 5.4.1 Coefficients, lines, and lines() 93
  • 5.4.2 Expanded grids, prediction, and a more generic model plotting method 94
  • 5.4.3 The final picture 99
  • 5.4.4 An analysis workflow 101
  • Chapter 6 Final Comments and Encouragement 105.