Reproducible Research with R and R Studio

Christopher Gandrud

July 15, 2013 by Chapman and Hall/CRC
Reference - 294 Pages - 33 B/W Illustrations
ISBN 9781466572843 - CAT# K16624
Series: Chapman & Hall/CRC The R Series

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  • Presents straightforward examples to illustrate a reproducible research workflow, from data gathering to the presentation of results
  • Uses the integrated developer environment RStudio
  • Shows how to automatically generate tables and figures using R
  • Discusses the R package knitr for literate programming
  • Provides instructions on formatting a presentation document via markup languages
  • Describes cloud storage and versioning services such as Dropbox and Git/Github
  • Explains how to use Unix-like shell programs for working with large research projects
  • Offers examples and a reproducible research project available for download on the author’s website


Bringing together computational research tools in one accessible source, Reproducible Research with R and RStudio guides you in creating dynamic and highly reproducible research. Suitable for researchers in any quantitative empirical discipline, it presents practical tools for data collection, data analysis, and the presentation of results.

With straightforward examples, the book takes you through a reproducible research workflow, showing you how to use:

  • R for dynamic data gathering and automated results presentation
  • knitr for combining statistical analysis and results into one document
  • LaTeX for creating PDF articles and slide shows, and Markdown and HTML for presenting results on the web
  • Cloud storage and versioning services that can store data, code, and presentation files; save previous versions of the files; and make the information widely available
  • Unix-like shell programs for compiling large projects and converting documents from one markup language to another
  • RStudio to tightly integrate reproducible research tools in one place

Whether you’re an advanced user or just getting started with tools such as R and LaTeX, this book saves you time searching for information and helps you successfully carry out computational research. It provides a practical reproducible research workflow that you can use to gather and analyze data as well as dynamically present results in print and on the web. Supplementary files used for the examples and a reproducible research project are available on the author’s website.