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 is a beautiful story from Reddit, with a very kind Redditor, Higgnenbottoms/Quoc Tran, who shared his data with all of us, so we can use this as an example of a) independent t-tests, b) violin plots, AND R. So, user r/quoctran98 wanted to know if Daves knew more Daves than non-Daves do. HA! He started by collecting data from r/samplesize . Do you all know about that subreddit, where you can post a survey and see who responds? You're welcome. Anyway, Quoc analyzed his data AND created a violin plot to illustrate his data. He shared it at r/dataisbeautiful , which is another excellent stats subreddit. See below. AND...here is the kicker...I contacted Quoc, and he shared his data (so your students can run their t-tests) AND his R code . I cleaned up his data a bit to provide the same results as the graph above (he had someone report that they knew 69 Daves. I mean, he collected the data from Reddit users.).