The thing about my way of teaching stats is that my cool, novel examples get old really fast. Like, pop culture is on a thirty-day cycle. Anyway, YEARS ago, 2014 to be exact, I blogged about illustrating bimodal data distributions using baby name data from the Social Security Administration. Specifically, when an older name comes back into vogue, it has a bimodal distribution when you plot time on the X axis. I stand by this example. However, all of the data illustrations come from 2014. When our traditionally aged college students were 6 or 7. Which makes this example feel a little stale. However, here is some data, courtesy of Redditor fevaah , showing old names that are back in vogue through 2025 ! And Eleanor, Violet, Nora, and Hazel are here, illustrating bimodal distributions for a new generation. If you used my old baby-name data, this is a quick, easy refresh for your lectures (or a fun new addition if you didn't). If this idea was help...
This one is for all of my psychometric instructors.
CNN created an engaging, interactive website to explain rank choice voting using ice cream flavor preference. It was created due to the 2025 NYC mayoral primaries, but uses ice cream instead of humans to make for a good explainer that may have a home in your classroom.
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| https://www.cnn.com/interactive/2025/06/politics/ranked-choice-voting-explained-dg/ |
First, you rank order your top five favorite ice cream flavors out of a field of ten.
Then, you can view all users' ranking data, and see how the distribution changes when the least popular flavor, Rocky Road, is eliminated and the rocky road voters' votes are redistributed.The vote relocation goes on and on...
Rank-choice voting is one of those concepts that is easier to explain with a bit of animation and a very simple premise. I couldn't capture it in my screenshots, but the flavor elimination and redistribution are animated. It's a small detail, but it really helps clarify the concept.
If you like this example, check out my W.W. Norton & Co. textbook, Psychological Statistics for Everyone.




