Learn R (open source statistical software) this summer with SWIRL!

Computer-headed figure by Keith Haring

R is quickly becoming the preferred software for statistical analysis. It is free, open source, and has a broad international following. Though the landing page for “The R Project for Statistical Computing” is nothing flashy, the software is worth the effort to learn. If you already use SPSS or Stata, the leap to R is not large.

SWIRL, the interactive teaching tool for R, makes it relatively easy to learn the logic (e.g., atomic vectors vs. list vectors), command prompts and syntax (e.g., c() = concatenate), and broad-ranging functions of R. SWIRL operates within R—or RStudio, if you’d prefer—and takes you step-by-step through basic features and advanced programming (e.g., designing your own functions). The SWIRL program was created by educators “passionate about statistics,” and it is both engaging and concrete.

Step 1: R vs. RStudio: Don’t choose; download both!

R and RStudio are the two front-ends of a powerful back-end statistical software program. RStudio is the Integrated Development Environment (IDE), or more user-friendly interface for R. It opens as a multi-paned window that enables browsing of data, programming, and other features to occur side-by-side. Laptop users with small screens might find this arrangement suboptimal, as will advanced programmers who might prefer the basic R console. Since R and RStudio download relatively quickly and aren’t large files (e.g., compared to ArcGIS), download both and choose for yourself!

Download R: http://www.r-project.org/

Download RStudiohttp://www.rstudio.com/products/RStudio/

When you download R, you will need to select a mirror site. Choose one near your current location, but don’t overthink it (i.e., guess; don’t geo-triangulate).

Step 2: Install SWIRL and Go!

SWIRL takes moments to install; instructions are on the SWIRL student page. Once the package is installed and you have executed the library(“swirl”) function, you will be able to complete scaffolded lessons such as R Programming: The basics of programming in R, and Regression Models: The basics of regression modeling in R. A narrator, of sorts, will guide you through the lessons. S/he is quite encouraging and a bit humorous. You might not even mind whiling away the summer with the SWIRL narrator, though you needn’t admit it.

To learn more about R, see examples of code, etc.:

1. IDRE/UCLA, Resources to help you learn and use R    

2. RStudio, Online learning 

3. Flavio Barros, MOOCs and courses to learn R 

4. James Gareth, An introduction to statistical learning with applications in R [eBook]

Image: New York subway drawings: Computer-headed figure by Keith Haring. Courtesy of Yale Digital Images Gallery. 

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