7 Concluding Remarks
My hope is that this book provides a nice introduction into understanding how statisticians, data scientists, and many other professionals use RStudio and R Markdown to simplify their analyses and ensure that their reports are computationally reproducible. Learning R is not nearly as intimidating as it once was, and more and more industries are shifting towards free open-source tools like R and RStudio. R Markdown provides an excellent way to document your analyses and share it with others in a variety of formats.
Of course, this book is just the tip of the iceberg in terms of showing you what R can really do. If you’d like to learn more, I encourage you to check out Modern Dive, a free, online, open-source book Albert Kim and I wrote on using modern data analysis techniques and visualization with R, RStudio, and R Markdown.
Additionally, Garrett Grolemund’s “Hands-On Programming with R” (Grolemund 2014) is an excellent resource and goes into much more depth than I do here on how to work with more complicated objects in R. It also discusses concepts in a project-based framework that is entertaining and easy-to-read.
As always, feel free to send me an email at firstname.lastname@example.org if you’d like any further clarification or if you have suggestions on improvements. Thanks for taking the time to read through this and best wishes to you on your next steps towards reproducible, thoughtful, beautiful analyses!
Grolemund, Garrett. 2014. Hands-on Programming with R. O’Reilly.