Install RStudio by dragging the application icon to your Applications folder.

Download R from (click on “Download R for Mac OS X” > “R-2.x.x.pkg (latest version)”).

Install R, RStudio, and R Commander in Mac OS X

If you get permission errors while installing packages, close R Studio and reopen it with administrator privileges.

Wait while all the parts of the R Commander package are installed.

Select the first option (or finish typing Rcmdr), ensure that “Install dependencies” is checked, and click “Install”. Start typing “Rcmdr” until you see it appear in a list.

Choose the location closest to you (probably “USA CA 1” or “USA CA 2”, which are housed at UC Berkeley and UCLA, respectively). R will download all necessary files from the server you select here. The first time you’ll do this you’ll be prompted to choose a CRAN mirror.

Go to the “Packages” tab and click on “Install Packages”.

Leave all default settings in the installation options.

Download R from (click on “Download R for Windows” > “base” > “Download R 2.x.x for Windows”).

Install R, RStudio, and R Commander in Windows The simple instructions below explain how to get everything working right. However, as is the case with lots of free and open source software, it can be a little tricky to install all of these different programs and get them to work nicely together. As intimidating as it might be to constantly type stuff at the console, it really is a lot faster.) (Lots of people (like me) use R Commander as a crutch for a few months before they get the hang of the R language. More advanced features of R aren’t accessible through R Commander, but you can use it for the majority of your statistics. It provides a series of menus that allow you to run lots of statistic tests and create graphics without typing a line of code. R Commander is a basic graphical user interface (GUI) for R. It’s basically a nice front-end for R, giving you a console, a scripting window, a graphics window, and an R workspace, among other options. RStudio is an integrated development environment (IDE) for R. Graphics created by R are extremely extensible and are used in high level publications like the New York Times (as explained by this former NYT infographic designer). It can run on pretty much any computer and has a very active and friendly support community online. R is an incredibly powerful open source program for statistics and graphics.

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