R is a free and open-source programming language well-suited for statistical analysis and data visualization. Various community-developed packages support a wide range of data science applications, including but not limited to machine learning, bioinformatics, geospatial analysis, and natural language processing.
Contents
Data Lab Resources
- Installing R and RStudio
- Introduction to the Statistical Programming Language R
- R for Data Manipulation and Visualization
Tufts University Courses
The following courses have been known to either teach or use the R statistical programming language. Please see departmental listings for details and SIS for current or future offerings.
- BIO-0132: Biostatistics
- BIO-0133: Ecological Statistics and Data
- CEE-0152: Environmental Health Data Lab
- CEE-0156: Biostatistics
- CS-0152-SBI: Statistical Bioinformatics
- DATA-0200 Foundations of Data Analytics
- ENV-0170: Environmental Data Analysis and Visualization
- ES-0025: Environment and Technology
- ES-0056: Probability and Statistics
- UEP-0236: Spatial Statistics
Udemy Courses
Tufts provides all affiliates with free access to Udemy Business, an online learning platform with curated on-demand courses. To access the platform, navigate to tufts.udemy.com, click on Continue with SSO, and then log in with your Tufts credentials. The platform is also accessible via the Udemy Business mobile application available on the Apple App Store and Google Play.
- R Programming A-Z
- Data Science and Machine Learning Bootcamp with R
- R Programming for Statistics and Data Science
- Advanced Analytics in R For Data Science
External Resources
The following resources are not affiliated with or endorsed by Tufts University but they have been reviewed by the Data Lab team and determined to be of high quality and relevant to the Tufts University community.
- swirl – Learn R programming interactively by completing hands-on courses right in the R console!
- RYouWithMe – A series of comprehensive online R learning resources aimed at beginners.
- Posit Primers – Interactive tutorials covering all aspects of using R for data analysis and visualization.
- Welcome to Shiny – Hands-on online tutorial on developing interactive applications using R Shiny.
- Quick-R – Useful references for experienced Stata, SAS, and SPSS users looking to transition into R.
- R Graph Gallery – Collection of data visualizations with corresponding R code.
- UCLA R Resources – Comprehensive collection of R resources by the Statistical Consulting Group at UCLA.
- CRAN Task Views – Subject-specific collections of useful R packages.
Free Online Books
The following comprehensive books are all freely available online with paper copies available for purchase.
Introductory
- R for Data Science – Undoubtedly the most popular introductory R book out there.
- Hands-On Programming with R – Less focused on data science and full of hands-on examples.
- R Markdown: The Definitive Guide – Comprehensive overview of using R Markdown for content creation.
Intermediate
- ggplot2: Elegant Graphics for Data Analysis – Comprehensive overview of the popular R graphing library.
- R Graphics Cookbook – Quick examples covering several different graphing libraries and plot types.
- Tidy Modeling with R – A modernized introduction to statistical modeling and analysis using R.
- Mastering Shiny – Comprehensive overview of using R Shiny to generate interactive data dashboards.
- Statistical Inference via Data Science: A ModernDive into R and the Tidyverse
Advanced
- Advanced R – Intended for intermediate R users looking to improve their skills and understanding.
- R Packages – Comprehensive guide to developing and publishing your own R packages.
- bookdown: Authoring Books and Technical Documents with R Markdown
Cheatsheets
Posit (the company behind RStudio) maintains a collection of various R cheatsheets. All cheatsheets are available for download in print-friendly PDF format with the most popular cheatsheets also available as websites. Below is a collection of the most relevant cheatsheets as determined by the Data Lab team. Please see the Posit Cheatsheets page for additional cheat sheets and various cheatsheet translations.
Introductory
Intermediate
- Data Import with the tidyverse
- Data Tidying with tidyr
- Data Transformation with dplyr
- Data Visualization with ggplot2
- String Manipulation with stringr
- Dates and Times with lubridate
- Factors with forcats
- Apply Functions with purrr