Statistical Graphics and Visualization course materials

I’ve just finished teaching the Fall 2015 session of 36-721, Statistical Graphics and Visualization. Again, it is a half-semester course designed primarily for students in the MSP program (Masters of Statistical Practice) in the CMU statistics department. I’m pleased that we also had a large number of students from other departments taking this as an elective.

For software we used mostly R (base graphics, ggplot2, and Shiny). But we also spent some time on Tableau, Inkscape, D3, and GGobi.

We covered a LOT of ground. At each point I tried to hammer home the importance of legible, comprehensible graphics that respect human visual perception.

Pie chart with remake

Remaking pie charts is a rite of passage for statistical graphics students

My course materials are below. Not all the slides are designed to stand alone, but I have no time to remake them right now. I’ll post some reflections separately.

Download all materials as a ZIP file (38 MB), or browse individual files:

Please note:

  • The examples, papers, blogs and researchers linked here are just scratching the surface. I meant no offense to anyone left out. I’ve simply tried to link to blogs, Twitter, and researchers’ websites that are actively updated.
  • I have tried my best to include attribution, citations, and links for all images (besides my own) in the lecture slides. Same for datasets in the R code. Wherever I use scans from a book, I have contacted the authors and do so with their approval (Alberto Cairo, Di Cook, Mark Monmonier, Colin Ware, & Robin Williams). However, if you are the creator or copyright holder of any images here and want them removed or the attribution revised, please let me know and I will comply.
  • Most of the cited books have an Amazon Associates link. If you follow these links and buy something during that visit, I get a small advertising fee (in the form of an Amazon gift card). Each year so far, these fees have totaled under $100 a year. I just spend it on more dataviz books 🙂

2 responses to “Statistical Graphics and Visualization course materials

  1. Thanks for sharing your course materials! Nice to see that you discussed the static grammar of graphics (ggplot2) and interactive graphics (D3). However I was disappointed to see that you did not mention which combines the two, greatly simplifying design of interactive graphics (write no JavaScript, only R/ggplot2 code + clickSelects + showSelected interactive aesthetics). I suggest you consider adding a discussion of Animint if you ever teach another course on interactive graphics.

    • Thanks, Toby. I did mention animint briefly in class and the slides. (In the lecture 07 slides, it’s listed as an alternative to try out in the next lab session—but I could have mentioned it in the 08 lab slides too.)

      Teaching what I already know myself, for interactive graphics I focused on Shiny this time. But I’d like to practice more with animint (and also ggvis) for future courses.