
Getting Started with R An Introduction for Biologists
by Beckerman, Andrew P.; Petchey, Owen L.-
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Summary
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 Statistics 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 |
Table of Contents provided by Ingram. All Rights Reserved. |
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