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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.
- Sales Rank: #1045916 in eBooks
- Published on: 2013-07-15
- Released on: 2013-07-15
- Format: Kindle eBook
Review
"… a very practical book that teaches good practice in organizing reproducible data analysis and comes with a series of examples. … an extremely valuable overview of the current capabilities of R, RStudio, and related software tools for reproducible research. I recommend this book to anyone who wants to learn more about these fascinating tools."
―Biometrical Journal, 2014
"Gandrud has written a great outline of how a fully reproducible research project should look from start to finish, with brief explanations of each tool that he uses along the way. … the readers who will get the most use from this book are those are already working in R and just need a way to organize their work. That being said, advanced undergraduate students in mathematics, statistics, and similar fields as well as students just beginning their graduate studies would benefit the most from reading this book. Many more experienced R users or second-year graduate students might find themselves thinking, ‘I wish I’d read this book at the start of my studies, when I was first learning R!’ … a good text for beginning graduate students or advanced undergraduate students who are just starting to do technical research. … This book could be used as the main text for a class on reproducible research …"
―The American Statistician, November 2014
"Three recent books have significantly influenced how I use R in reproducible work: Dynamic Documents with R and knitr by Yihui Xie, Reproducible Research with R and RStudio by Christopher Gandrud, and Implementing Reproducible Research edited by Victoria Stodden, Friedrich Leisch, and Roger D. Peng … I recommend all three books to R users at any level. There really is something here for everyone."
―Richard Layton, PhD, PE, Rose-Hulman Institute of Technology, Terre Haute, Indiana, USA
About the Author
Christopher Gandrud is a research associate at the Hertie School of Governance. He was previously a lecturer of international relations at Yonsei University and a fellow in government at the London School of Economics (LSE). He has published articles on political economy and quantitative methods in the Review of International Political Economy and the International Political Science Review. He earned a PhD in political science from the LSE.
Most helpful customer reviews
2 of 2 people found the following review helpful.
Required reference
By John Mount
Christopher Gandrud's "Reproducible Research with R and RStudio" is a very useful book and well written. It serves at least three important purposes: it pushes the reproducible research agenda (providing the ability for the original researcher or others to be able to re-run and confirm work in the future), it gives a good selection and overview of critical tools in and near the R ecosystem (R, RStudio, knitr, git, latex, Markdown), and describes some good work habits (such as the directory layout suggested on the cover). This isn't strictly a book on R, analytics, or data science. It is an introduction to the tools that make the work of an R user, an analyst, or a data scientist easier to do (and easier to re-do later).
I mostly use the book as a reference. What this book reminds me of in spirit is Birns' "Unix for People: A Modular Guide to the Unix Operating System : Visual Editing, Document Preparation and Other Resources" 1984. I am working from old memory here: but people who had access to Birns' book (or one like it) could immediately start producing research papers on Unix (likely using vi, troff, and the classic Unix text tools). It (and the current book) gave a quick overview of the tools most likely to help you perform your own work well using current tools.
Note: there seem to be a lot of reported issues of legibility on this book. Obviously buyers deserve a legible copy of a book they paid for. My copy is perfectly legible (ink is fully dark), though the font size is a touch on the small side.
1 of 1 people found the following review helpful.
Outstanding
By A Student
One of the best things about this book is that Gandrud does an excellent job in introducing the reader to a wide variety of tools (R, Git, knitr, Make, LaTeX) in a simple manner such that those who are not familiar with these tools should be able to grasp the material quite easily. I already knew R and LaTeX but was unfamiliar with Git and Make, and I had no trouble reading about these. Furthermore, the author provides suggestions for further reading for those who want to know more about a certain topic (The Linux Command Line, for instance).
I'd strongly recommend this book for those who are familiar with the tools it covers but lack the knowledge on how to integrate them together in order to improve their project management skills. This book fills a gap that other, more specialized books, leave open.
I had to take off a star because like another reviewer said, the examples are printed in very light text that is difficult to read. I don't know how much control the author has over the book's appearance but this is an issue I believe needs to be addressed. Otherwise, it was a book that I looked forward to reading each day when I was working through it.
3 of 5 people found the following review helpful.
great book for learning how to do reproducible research
By BookBuyer
I've known about the various "reproducible research using R" tools for a while but this book is going to be amazing as far as tieing them all together. I've been an emacs-ess/Sweave fan for a long time. My guess is that this book will force me to finally move to the other side. I've only read the first chapter and skimmed the rest of it because of time constraints at the moment(I plan on coming back to it ASAP and reading the rest carefully ) but I have enough experience with skimming to be very certain that it will be a hit in the R community. Thank you Christopher. I've been hoping for something like this for a LOOOOOOOOOOOOOOOONG time.
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