7 Concluding Remarks
I hope that this book provides a nice gateway into understanding how statisticians, data scientists, and many other professionals use RStudio and R Markdown to simplify their analyses and to ensure that their reports are computationally reproducible. Learning R is nowhere near as intimidating as it used to be 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 Albert Kim and I’s online, free, open-source book on using modern data analysis techniques and visualization with R, RStudio, and R Markdown. More details on that project will be coming soon.
Additionally, Garrett Grolemund’s “Hands-On Programming with R” (Grolemund 2014) is an excellent resource and goes into more depth than I do here as to 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 email@example.com 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.