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...
Annual snow fall moderates the relationship between daily snow fall and the likelihood of canceling school
Moderation isn't one of those things that we typically teach in Intro Stats. But it is a statistical tool your advanced undergraduates will likely encounter in an upper-level course. I'm not going to teach you how to teach your students how to do one. I am, however, going to share a example of what mediation is doing, inspired by living in the city in the US that has received the most snow this season (Erie, PA, with 93.9 inches for the season as of 1.30.25). About a year ago, CNN shared data on how much snow it takes to cancel school in various parts of the country. I assure you, Erie and the rest of Northwest PA (see red outline) gets hella snow but no snow days. https://www.cnn.com/2024/02/12/us/how-much-snow-kids-school-snow-day-across-us-dg/index.html However, our lack of snow days isn't due to lack of snow. The annual amount of snow moderates the likelihood to cancel school, such that if you are used to a lot of snow (and have the infrastructure to handle it) you d...