If you are a Windows user, please disregard any warnings that appear about RTools.
Learn how to combine the best ideas of reproducible research into a simple, easy to use workflow with R. Do you know that R can do more than analyze your data? R provides an easy way to report your results and make your research reproducible. This tutorial will teach you how to use R’s reporting power with three R packages:
The Packrat package automatically captures the dependencies of your code when you run it, making sure that you can exactly reproduce results in the future. With Packrat, you can always rerun your script in its original computing environment, even if the packages used by your script have been replaced or updated.
The R Markdown package builds dynamic documents, presentations, and reports straight from your code. It combines the core syntax of markdown (an easy-to-write plain text format) with embedded R code chunks that are run so their output can be included in the final document. R Markdown documents are fully reproducible (they can be automatically regenerated whenever underlying R code or data changes) and completely dynamic (you can export an R Markdown document as an html, pdf, or MS Word file, or a slide show).
The Shiny package creates an interactive dashboard for your analyses. With Shiny, you can let readers use your reports to explore, customize, and stress test your results. Readers can modify parameters, update data sets, and make other changes that will immediately propagate through the models, tables, and plots of your report.
Together these packages create a reporting pipeline that makes it easy to reproduce your research and communicate your results in an engaging way. We will examine this pipeline and practice using it with a series of exercises and instructor-led examples.
Garrett is the editor-in-chief of shiny.rstudio.com, the development center for the Shiny R package, and is the author of Hands-On Programming with R as well as Data Science with R, a forthcoming book by O’Reilly Media. Garrett works as a data scientist and chief instructor for RStudio, Inc.
Colin Gillespie is a statistician and an associate professor at Newcastle University, UK, where he works on computational statistics, big data problems, and scalable Bayesian inference. He has taught courses on R for over ten years, attracting participants from around the world.
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