Help pages

The main reference in R is the built-in help system. For example, typing

?read.table

?plot

will not only explain how those two functions work, with examples, but also provide cross-references to related help pages. This usually solves specific problems that arise when using R. Other ways to find help pages include:

apropos("plot")

help.search("plot")

help(package="graphics")

Manuals

An Introduction to R is the official R user manual, covering similar topics as the first day of our workshop (data objects, input/output, linear models, plots, packages), as well as writing your own R functions. It is not written as a tutorial for the absolute beginner, but as a reference for someone who already knows the basics of R and would like to learn more.

User-contributed tutorials are generally written in a less technically challenging style. Among the many contributions are two compact reference cards, and tutorials in non-English languages. The tutorial by Longhow Lam seems especially approachable.

Technical manuals by the R development team cover topics like import/export and R configuration in great detail.

Books

There is a wealth of books related to R. If you use R a lot, you will probably end up buying a book or two, but the free manuals and help pages are enough to learn the basics.

Journals

The R Journal and the Journal of Statistical Software are both peer-reviewed journals dedicated to the use of R.

Open source

For experienced R users, the ultimate reference on how a statistical method works is to look at the function source code. For example, typing

lm

will show the exact calculations behind linear models in R.

This access to the source code is of critical value for more complex statistical models. Open source principles (making a thorough description of methods publicly available) have been a foundation of scientific research for centuries.

Web

Sometimes the quickest path to solving an R problem is a normal web search in your browser, which will cover the FAQ and several mailing lists. Another approach is to search specific websites from R by typing:

RSiteSearch("plot")