Getting Started with R: An Introduction for Biologists

by Andrew P. Beckerman, Dylan Childs, Owen Petchey

R is rapidly becoming the standard software for statistical analyses, graphical presentation of data, and programming in the natural, physical, social, and engineering sciences. Getting Started with R is now the go-to introductory guide for biologists wanting to learn how to use R in their research. It teaches readers how to import, explore, graph, and analyse data, while keeping them focused on their ultimate clearly communicating their data in oralpresentations, posters, papers, and reports. It provides a consistent workflow for using R that is simple, efficient, reliable, and reproducible.This second edition has been updated and expanded while retaining the concise and engaging nature of its predecessor, offering an accessible and fun introduction to the packages dplyr and ggplot2 for data manipulation and graphing. It expands the set of basic statistics considered in the first edition to include new examples of a simple regression, a one-way and a two-way ANOVA. Finally, it introduces a new chapter on the generalised linear model.Getting Started with R is suitable for undergraduates, graduate students, professional researchers, and practitioners in the biological sciences.

Genres: Science, Nonfiction, Textbooks, Reference

258 pages, Kindle Edition

First published March 7, 2012

Reviews

[Wendelle · Rating 5 out of 5]

It is really, really good for total beginners like me. It will dedicate sentences to tell you which button to click, which pane to look at and provide you a massive dataset instead of having you experiment on one you have to make yourself. However, some of the codes don't seem to work.

[Kaveh · Rating 5 out of 5]

I never thought I would learn my first programming language by reading a book, rather than taking an online course, a workshop, or by bugging a colleague who has some strong coding muscles. This book is tailored for biologists and it's an excellent step-by-step guide for building the fundamental skills in using R for data analysis and visualization. Midway through the book, I had already figured how to learn by myself, and that's the greatest skill in any learning process. The "ggplot2" section was the most important module for me, but that said, the other three sections are equally useful and important.

[Sarah · Rating 3 out of 5]

This book provides a very nice, basic introduction to R with accessible biological examples. You can work along with the authors, which is very nice. Having tried & somewhat failed to dabble in R with just a background of basic programming skills but nothing R-specific, this book was a perfect grounding point. Now I can approach R very logically and with the statistical mindset that I need to conduct my analyses. I would recommend this book! It's also pretty short & easy to read, so that's good.