Getting Started with R by Andrew BeckermanGetting Started with R by Andrew Beckerman

Getting Started with R

byAndrew Beckerman, Owen Petchey, Dylan Childs

Paperback | February 3, 2017

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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 theirresearch. It teaches readers how to import, explore, graph, and analyse data, while keeping them focused on their ultimate goals: clearly communicating their data in oral presentations, 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 firstedition 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.
Andrew leads a research team studying community and evolutionary ecology. He has been using R and teaching quantitative methods for over 16 years. Owen leads a research team studying ecological forecasting. He has been using R and teaching quantitative methods for over 16 years. Dylan leads a research team studying population biology....
Title:Getting Started with RFormat:PaperbackDimensions:240 pages, 9.45 × 6.61 × 0 inPublished:February 3, 2017Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0198787847

ISBN - 13:9780198787846

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Table of Contents

Preface1. Getting and getting acquainted with R2. Getting your data into R3. Data management, manipulation, and exploration with dplyr4. Visualising your data5. Introducing statistics in R6. Advancing your statistics in R7. Getting started with generalised linear models8. Pimping your plots: scales and themes in ggplot29. Closing remarksAppendices

Editorial Reviews

"I was engaged by the refreshing style of the authors, that while informal, gives the user clear step-by-step instructions for using the software. Apart from the clear biological leaning of the example data, this book is applicable to anyone learning R (even a statistician!)." --Significance