Quick Start Guide for R

Have you decided you’d like to learn R, but aren’t sure where to start? This page will give you some guidance about some of the resources that are available, on this site and beyond!

Arcus Education has a variety of articles and learning modules to help you get started:

• Getting started (installing R and learning the basics):
  • For a curated list of learning modules related to R (and a variety of other topics), see the Suggested Learning Modules page of the DART website and scroll down to Pathway 4: Analysis in R (if you are curious about the DART program and research study, check out the DART home page). This pathway will take you from a general discussion of why you might want to choose R, how to download R to your own computer, all the way through data visualization, analysis, and even some opportunities to practice!
• Reproducible analysis
  • Why Use Literate Statistical Programming?
  • Scripted Analysis for Reproducibility
  • Literate Statistical Programming
  • R Markdown 101
  • R Lab for Beginners
• Creating visualizations:
  • Base R Plotting
  • ggplot Overview
• Data transformation:
  • Data Combining in R
  • Date Pairing in R
• “Intermediate” R topics:
  • Code Readability (useful for R or any other programming language!)
  • Ordinary Linear Regression in R
  • Tiny Munge
  • Sparklines in ggplot2
  • Customizing ggplot2 with ggThemeAssist
  • When R Gets Too Helpful
  • Regex (also known as regular expressions, regex are not R-specific- but can be very useful!): Demystifying Regular Expressions and Regex 101.

Besides the articles and modules available here, there are many more resources out there! Here are a few of our favorites:

• R for Data Science- A free online book by Hadley Wickham and Garrett Grolemund that teaches data science using R and starts from the very beginning.
• RStudio primers- They have bite-sized lessons starting with programming basics and going through topics like writing reproducible reports and making web apps.
• R-Bootcamp- Similar to the primers, the R-Bootcamp has a lot of lessons centered around using ggplot2 and dpylr, which will help you practice data science skills in R.

And what about when you’ve worked through all of this, and are ready for the next steps?

• Join the CHOP R User Group, where you’ll become part of a supportive community of other R users at all levels of R expertise.
• Start your own project! Try automating a work task (start small!), or ask a research question using some public data sources like OpenDataPhilly, the Census Bureau, or Kaggle.
• Need more personalized advice? Ask for an educational consult by emailing dlarcuseducation@email.chop.edu.

Good luck on your R journey!