Tufts Resources
  • Download instructions: R and R Studio. Installation instructions for Windows and MAC.
  • A Gentle Introduction to R. This workshop is designed to get you started with the statistical programming language R. We provide an overview of the R language along with the RStudio interface. During the session, we use datasets built into RStudio to introduce importing data, performing descriptive statistics and making simple visualizations to get you familiar with working in R. This workshop is suitable for those who have not worked with R/RStudio before. You can listen to a recording of this workshop here: Intro to R 02-02-2018.
  • R and RStudio Basics. This tutorial is designed to get you started with the statistical programming language R and the RStudio Interface. We provide a detailed overview of the RStudio IDE and its functionality. We will guide you through setting a working directory, installing and loading R packages, opening and running scripts, and using R documentation from the Help Tab. We will also create, view, and manipulate the most common types of R data structures (atomic vectors, lists, matrices, and data frames).
  • Web Scraping with R. This workshop provides an introduction to web scraping – the process of extracting data (tables and texts of all kinds) from websites – with R.
  • Intermediate Statistics in R – From Surveys to Statistics:  This workshop dives deeper into the process of analyzing survey data with R and RStudio using the Demographic and Health Survey Children’s Recode data.
External Resources
  • RStudio CheatsheetsRStudio cheat sheets are great references for learning and using R packages. Some of the cheat sheets we use the most are: Data Transformation, and Data Visualization.
  • CRAN Task Views. Task views are helpful for navigating R packages. They give a brief overview of packages on specific topics and allow automatic installation.
  • UCLA’s R Website. A comprehensive site to help you learn and use R by the Institute for Digital Research and Education at UCLA. This site has tutorials, examples, web books, annotated outputs, and best practices.
  • R for Data Science. This book will teach you the best practices for importing, wrangling, visualizing, exploring, and modeling data.
  • Quick-R. This website is tailored for experienced users of other statistical packages (e.g., SAS, SPSS, Stata) who would like to transition to R.
  • Analyze Survey Data. A resource for survey data analysis methodologies in R.
  • Beautiful plotting in R. This website walks you through creating plots using the ggplot2 package. This package is fantastic for creating graphics in R.
  • Learn Shiny. Shiny has good tutorials for getting started with this R package. Shiny makes it easy to build interactive web apps straight from R. Take a look at the Gallery for examples of web apps built using Shiny.