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...
Explain validity to your students AND earn some "I'm still hip!" street cred using this The Tonight Show clip that features a Buzzfeed quiz AND exactly one Jonas brother. Nick Jonas took a "Which Jonas Brother are you?" Buzzfeed quiz. He scores as Joe Jonas. Ergo, the Buzzfeed assessment measure is not valid. It does not properly assess what it purports to assess. Watch the video for yourself. If you want to take this example a step further, you could have your students take the original quiz, discuss the questions and their ability to discern which Jonas Brother is which, you could describe Nick Jonas as a Nick Jonas Subject Matter Expert, maybe Social Desirability got in the way of Nick answering the questions honestly, etc. Another thing I've noticed as my blog and I have aged together: There are now generations of Buzzfeed quiz assessments that provide great examples for different age groups: Gen X: Shirley Manson did not score as Shirley ...