We use R for most statistical analyses. To help ourselves and others, here is a list of the R resources we find most useful.
Dan's R Cheat Sheet: a 2-page summary of the functions I use the most.
Cheatsheets by RStudio: info-packed 2-page guides for graphing, data wrangling, markdown, etc.
Markdown Cheatsheet: a quick reference for markdown syntax.
Quick-R: an excellent searchable reference guide
Cookbook for R: cookbook-style how-to wiki, particularly useful for experimental psychology
Matlab/R Reference guide: A handy reference for both R and Matlab (our other main analytical tool)
Hadley Wickham's Style Guide
ggplot2: documentation website for our main graphics tool
A nice guide to themes.
The R graph gallery: many different graph examples with snippets of code for generating them.
Data Visualization: A practical introduction by Kieran Healy: uses ggplot2 and includes code and data sets.
Fundamentals of Data Visualization by Claus O. Wilke: focuses on principles for creating accurate, effective, and attractive visualizations; does not include code
Primers that cover the most important aspects of using R and programming with R (by the RStudio team)
For absolute beginners who want a gentle (or silly) introduction
R for cats: a basic introduction to R, particularly good if you have no programming experience (and like cats).
DataCamp Introduction to R: Online interactive tutorial that covers the basics (intro is free, additional courses require membership fee)
Intro to R: a series of short videos (2-6 minutes) demonstrating basic R tasks or concepts
Learn R Programming: a good introductory R programming tutorial
For beginners who want a more comprehensive guide
For intermediate users who are familiar with command line interfaces and want to learn R
APS guide to Learning to Work With R
Resources to help you learn and use R: from the Institute for Digital Research and Education at UCLA
R Bloggers: A blog aggregator pulling together posts from over 140 bloggers who write about R in English
StackOverflow - R: A great community Q & A site. If you have a problem, they can usually help you.
YaRrr! A Pirate's Guide to R by Nathaniel D. Phillips (free ebook)
Applied R for the quantitative social scientist by Rense Nieuwenhuis (free pdf)
Statistical Inference via Data Science: A ModernDive into R and the Tidyverse by Chester Ismay and Albert Y. Kim (free ebook)
R for Data Science by Hadley Wickham and Garrett Grolemund (free ebook)
R in a Nutshell by Joseph Adler
R for SAS and SPSS Users by Robert Muenchen
Analyzing Linguistic Data by Harald Baayen
Books that teach statistics and R together:
Statistical Thinking for the 21st Century by Russell Poldrack (free ebook)
Learning Statistics with R by Dani Navarro (ebook is free)
Discovering Statistics Using R by Andy Field, Jeremy Miles, & Zoe Field