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...
File under: End of the semester stress blogging about a person who brings me joy. Taylor Swift (see: sampling error with Taylor ). Here is a new, VERY accessible example of ordinal data . Rob Sheffield, writing for Rolling Stone, rank-ordered ALL of Dr. Swift's songs. https://www.rollingstone.com/music/music-lists/taylor-swift-songs-ranked-rob-sheffield-201800/bad-blood-2014-196114/ Also, introduce your students to Methods Section 😁. This rank order is based on the variable "Taylor genius". You could even use this as an example of anti-interrater reliability. This ranking comes from exactly one person. AND YOU'RE ON YOUR OWN KID DESERVED BETTER. Each ranking includes the best lyric from the song as well as a brief description of the Taylor Genius on display. Is this also an example of qualitative data? https://www.rollingstone.com/music/music-lists/taylor-swift-songs-ranked-rob-sheffield-201800/the-great-war-2022-1234617639/