I’m giving a short “unconference” on doing basic statistics with R at a Center for Applied Rationality minicamp I’m attending next week, and I’ll need participants to show up with R installed on their laptops along with a Rstudio. This is a short tutorial for participants to follow in order to get everything up and running.
First, go to R’s website, which should look something like this:
On the left hand side, click on the CRAN link under “Download, Packages” next to the arrow in the image above. This will bring up a page of links to download R from, like the image below. Choose a location close to you so that the download is faster.
This should bring you to a page that looks like the image below. Now click on the link to download R for whatever operating system you’re running. I.e. if your computer has Windows, click on “Download R for Windows.”
This should bring up another page with a few more links, like the picture below. Click on “base.”
Finally we get to the page with the actual download link, like below. Click on “Download R 2.15.1 for X” where X is whatever operating system you have.
This will download the executable to install R – a file named “R-2.15.1-win.exe” or something similar. Make sure you save it somewhere you can find it easily. When it finishes, run the file. Just follow the on-screen instructions that pop up. You shouldn’t have to change anything in order for R to properly install.
Now you’re all set to start using R… except the GUI that R comes with out of the box isn’t very good. Rstudio is a free IDE that improves on the base R GUI substantially. Go here to download it. Download the version of Rstudio that their website recommends for your machine somewhere that you can easily find. Once this completes, open the file – it should be called “RStudio-0.96.316.exe” or something similar. From this point, just follow the on-screen instructions to complete the installation.
That’s all the software you’ll need for my presentation! If you have some time it might be useful to poke around Rstudio to get a general feel for it, but you certainly don’t need to in order to understand my presentation. There are a few tutorials to guide your poking scattered about the web, including this one (warning: pdf).
EDIT: Here are a few more resources that will be useful. First, you’ll need an additional R package called arm – this package allows you to quickly fit Bayesian linear and generalized linear models. In order to install this, open up R Studio and make sure you’re connected to the internet. Then type install.packages(“arm”) into the R console, as below.
R will output the following message, or something similar:
Installing package(s) into ‘C:/Users/Matt/R/win-library/2.15’
(as ‘lib’ is unspecified)
— Please select a CRAN mirror for use in this session —
Wait for a few seconds, then R will give you some options for which mirror to download from. Type the number for the mirror that is closest to you to download everything faster, then press enter. See the picture below.
R should be pretty busy for a few minutes while it downloads and installs several packages that arm depends on as well as arm itself. Once it finishes and you see the blue “>” in the bottom of the R console, the packages are installed.
Futhermore, you’ll need another R package call “ggplot2”. You can install this using the same command: install.packages(“ggplot2”).
In addition, I’ve uploaded a dataset that we’ll be using during my presentation. Download it here. Save it as diam.csv somewhere you can easily find it.
So to be 100% ready for my presentation, you need to have installed R, R Studio, and the arm and ggplot2 packages, as well as have downloaded the data file diam.csv.
Finally, here are a few useful resources for before, during, and after my presentation:
An R script containing my entire presentation. Open with any text editor, though opening it in R Studio is best.
An R reference card. (pdf) Print it out and tape it on the wall next to your desk. Useful for after the presentation.
The ggplot2 website. This contains useful information for making complicated and informative graphics. Useful after the presentation.
Course website for the class I took to learn R. Some overlap, but there are many new things. Useful for after the presentation.