Links to resources I have found useful or think might be helpful to future me or R statisticians/data analysts/developers like me.
- bensstats
- ouR data generation
- R-bloggers.com
- r4stats.com - Bob Muenchen
- rOpenSci.org
- RWeekly.org
- StatsAndR.com
- Tidyverse.org
- Advanced R, 2nd ed - Hadley Wickham
- Advanced R Solutions - Malte Grosser, Henning Bumann, & Hadley Wickham
- Big Book of R: Package development recommendations
- Efficient R programming (2021) - Colin Gillespie & Robin Lovelace
- R Internals (official docs)
- R Packages, 2nd ed - Hadley Wickham & Jennifer Bryan
- Rcpp for everyone (2020) - Masaki E. Tsuda <- Using C++ in R
- Writing R Extensions (official docs)
- Analyzing Financial and Economic Data with R (2023) - Marcelo S. Perlin
- Applied Time Series Analysis for Fisheries and Environmental Sciences (2021) - E.E. Holmes, M.D. Scheuerell, and E.J. Ward
- Applied Microeconometrics with R (2024) - Achim Zeileis & Christian Kleiber
- Data Science for Economists and Other Animals (2021) - Grant McDermott and Ed Rubin
- Data Structures, Estimation and Optimization with R (2024) - Fan Wang
- Econometrics (2021) - Bruce Hansen - "I'm sharing here the last open-access version of the manuscript"
- Econometrics in R (2008) - Grant V. Farnsworth
- Financial Econometrics - R Tutorial Guidance (2021) - Yizhi Wang & Samuel Vigne
- Fisheries Catch Forecasting (2020) - Elizabeth Eli Holmes
- Forecasting: Principles and Practice (book: 2021 / ebook: 2025) - Rob J Hyndman and George Athanasopoulos (2nd ed used the "forecast" package; 3rd uses the "fable" package)
- Introduction to Econometrics with R (2024) - Christoph Hanck, Martin Arnold, Alexander Gerber, and Martin Schmelzer
- Introduction to Econometrics with R (2020) - Florian Oswald, Vincent Viers, Jean-Marc Robin, Pierre Villedieu, Gustave Kenedi
- Introduction to R for Econometrics (?) - Kieran Marray
- Introduction to programming Econometrics with R (2014) - Bruno Rodrigues
- Introductory Econometrics: Description, Prediction, and Causality (2023) - David M. Kaplan
- The Little Book of R for Time Series (2018) - Avril Coghlan
- Microeconometrics with R (2024) - Yves Croissant
- Principles of Econometrics with R (2016) - Constantin Colonescu
- R for Economic Research (2023) - J. Renato Leripio
- R Guide to Accompany Introductory Econometrics for Finance (2019) - Robert Wichmann and Chris Brooks
- Using R for Introductory Econometrics, 2nd ed (2020) - Florian Heiss & PDF <- Also shares Python and Julia editions!
- Advanced Data Analysis From an Elementary Point of View (2025) - Cosma Rohilla Shalizi
- An(other) introduction to R (2022) - Felix Lennert
- Big Book of R - "over 400 free, open-sourced [R] books" - Oscar Baruffa
- Coding Club: Creating an R Package (2022) - Lisa DeBruine
- Collection of assorted PDFs
- Datacamp R Documentation
- Data Science Desktop Survival Guide - Graham Williams
- Deep R Programming (2025) - Marek Gagolewski & Full PDF
- Hands-On Programming with R (2014) - Garrett Grolemund
- icebreakeR (2016) - Andrew Robinson
- Intro to Data Analysis (2023) - Michael Franke
- Intro to Modern Statistics, 2nd ed (2024) - Mine Çetinkaya-Rundel and Johanna Hardin & source files
- Intro to R (2024) - Alex Douglas, Deon Roos, Francesca Mancini, Ana Couto & David Lusseau & Full PDF
- An Introduction to R (2013) - Peter Haschke
- Introduction to R (2010) - Longhow Lam
- Introduction to Programming with R (2025) - Reto Stauffer, Joanna Chimiak-Opoka, Luis Miguel Rodríguez-R, Thorsten Simon, & Achim Zeileis
- Learning statistics with R: A tutorial for psychology students and other beginners (2019?) - Danielle Navarro
- Modern R With the Tidyverse (2022) - Bruno Rodrigues
- Official R manuals
- OpenIntro Stats textbook (2019) - David Diez, Mine Cetinkaya-Rundel, & Christopher Barr <- "Intro to Modern Statistics" (2024) above is a derivative of this
- Practical Regression and Anova Using R (2002) - Julian J. Faraway
- R for Data Science, 2nd ed - Hadley Wickham
- R Cookbook, 2nd ed (2019) - James (JD) Long & Paul Teetor
- The R Guide (2010) - W.J. Owen
- R Inferno (2011) - Patrick Burns
- R Programming for Data Science (2022) - Roger D. Peng
- R Tutorials (2016) - William King
- Ramarro: R for Developers (2014) - Andrea Spanò
- Simple R (2002) - John Verzani
- A Sufficient Introduction to R (2018) - Derek L. Sonderegger
- The Undergraduate Guide to R (?) - Trevor Martin
- Using R for Data Analysis and Graphics (2008) - J H Maindonald
- YaRrr! The Pirate’s Guide to R (2017) - Nathaniel D. Phillips
- R Graphical User Interface Comparison - Bob Muenchen <- He now works for Bluesky, so not unbiased
- Bluesky <- commercial product with free basic version
- Eclipse StatET: Tooling for the R language
- Jamovi
- JASP & Github
- R AnalyticFlow
- R Commander
- R-Instat <- Windows-only
- RKWard
- RStudio <- Most popular. Offers open-source version and paid/commercial version.
- Rattle: A Graphical User Interface for Data Science with R
- Roger Peng Youtube channel <- many of these are ~ 10 years old
- Open Courses: Free Data Science Training Courses (DataCamp.com)
- Resources to Help You Learn and Use R - UCLA
- Impatient R
- Computing for Data Analysis week 1 videos - Roger Peng, week 2, week 3, week 4 & Coursera course
- Data Analysis videos - Jeff Leek's Coursera course & lecture notes & Coursera course
- Beginner's guide to R: (6-part) Introduction (ComputerWorld) & Beginner's guide to R: Useful resources
- R Programming - Johns Hopkins University (Coursera)
- Rtips (2014) - Paul E. Johnson
- One Page R
- Twotorials.com (fun 2-min R tutorials)
- R for Beginners - Emmanuel Paradis
- Intro to Data Analysis - Hadley Wickham
- Linear Regression Models - Jeff Goldsmith
- R Programming Wikibook