I think my favorite topic we covered in ASHA this past winter semester was the “good visualizations, bad visualizations” topic, in which I showed the students some examples of some really good visualizations of data/information as well as some really bad ones.

Visualization of information is, in my opinion, overlooked in introductory (and advanced) statistics courses. It’s important to not only understand the analyses and the data behind the analyses, but it’s just as important to be able to convey the meanings and interpretations of the data in ways that make said meanings/interpretations easy to understand. This can be done very effectively and efficiently with a good visualization.

And it can be done very misleadingly with a poor visualization.

I think I’m going to incorporate a little unit (maybe a lab or two?) focusing on the importance of good visualization next time I teach a higher-level stats course. Even if I just give similar examples to the ones I gave in ASHA (as well as, of course, general guidelines for different types of common visualizations), I can at least get students thinking about the visual presentation of information and how important it can be.

Anyway.