Installing the Software
The first thing you should do is download the software R and an easy-to-use interface called RStudio. Both are free to use. The instructions are below.
Select one of the compiled distributions based on your operating system. There are versions for Windows, Mac, and Linux systems. If you have problems with download and installation, first check out the FAQ page. If that doesn’t help, please post your question in the course forum and I can try to help you. If you run the R interface, you’ll notice that it is no-frills software.
2) Download and install RStudio (get the free version, of course)
To make working with R a bit more friendly, I recommend also downloading RStudio. This software sits atop of R and provides you with some nice tools such as an editor for working with R source code. There are also panes for viewing your graphs, help pages, loaded variables, and text output.When first opening RStudio, you should see something like this screenshot
Learning R with "swirl"
The best way to learn R is to dive right in. If you have had some experience with programming, you'll get the hang of R pretty quick. If not, you'll need to spend more time working through these tutorial lessons (as well as the ones listed below). The package "swirl" is an R add-on that allows you to learn from and interact with the R console. Give it a try! Now that you have R and RStudio installed, open RStudio and enter the following three lines of code in the Console window (you do not need to include the ">")
> install.packages("swirl") > library("swirl") > swirl()
You should now be greeted with a prompt that says, "What should I call you?". After working your way through a few more prompts, install the course "R Programming: The basics of programming in R" and then choose "R Programming". Work your way through all 15 lessons (they're short). This is a great way to get a nice overall introduction to R. When we really dig into R in Lesson 2, I will assume that you are familiar with all of the information presented in these lessons.
Note: If you encounter any errors along the way, please don't hesitate to contact me and I'll help you get up and running.
Additional Online Tutorials
Need more practice with R? The first place I'd start is with a site called DataCamp. DataCamp makes an R interface that runs inside a browser window. It does have its limitations, but is a great learning tool (we'll even use it in our courses). DataCamp offers a free Introduction to R course that walks you through some of the basics. Check it out!
Another source for R tutorials is Lynda.com. Penn State has an agreement with Lynda.com whereby faculty and students can take courses for free. If you have your Penn State userID and password, you can use Lynda. I suggest you work through "Learning R" and "R Statistics Essential Training" (Lessons 1 & 2) by Barton Poulson.
A few more resources... These are more traditional training materials. That is, you read through the exercises and follow along in your own version of R.
A tutorial from the University of Georgia. I suggest working through Lessons 1-7, 14, & 15.
A site called "R Tutorial" contains some useful information in their lesson called R Introduction.
There are many more sites that can be found by just Googling "R tutorial". If you find one you like, please suggest it for addition to this list.