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...
Uncrustables consumption rates by NFL teams 1) do not vary by league, 2) do not correlate with 2023 wins
Many thanks to Dr. Sara Appleby for sharing this data with me!! I really enjoy silly data, like this one from Jayson Jenks, writing for The Athletic, which shows how many Uncrustables each team eats per week. Well, data from the teams that elected to participate and/or didn't make their own PB and Js. The whole article is fun, so give it a read. It makes sense that hungry athletes would go for a quick, calorie-dense, nostalgic snack containing protein. Here is the data visualization: Damn, Denver. I entered this data into a spreadsheet for all of us. Spoiler alert: The number of Uncrustables eaten per week does not vary by league (independent t -test example), and the number of wins in 2023 does not correlate with the number of Uncrustables eaten per week in 2023 (correlation/regression example). Also, for my own curiosity, I re-ran the data after deleting Denver, and it wasn't enough of a difference to achieve significance.