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...
I have shared AMPLE examples for teaching correlations . Because I've got you, boo. Like, I have shared days' worth of lecture material with you, my people. I am adding one more example. I have used this example in my positive psychology course for years, and it really illustrates what can happen en masse when marketing departments and less-savory pop-psych elements try to establish causal relationships with features (stereotypes?) of happy countries and individuals' subjective well-being. I like this one because it is math-free, UG-accessible, and not terribly long. Joe Pinsker, writing for the Atlantic, argues that... https://www.theatlantic.com/family/archive/2021/06/worlds-happiest-countries-denmark-finland-norway/619299/ TL;DR: Just because Northern European nations consistently score the highest on global happiness data doesn't mean that haphazardly adopting practices from those countries will make you happy. Correlation doesn't equal causation. H ere is the ...