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...
Hey! I'm giving a keynote at the February annual teaching pre-conference at the Society for Personality and Social Psychology conference. It's all about social psychology stats example. Like this one! This one demonstrates social comparison theory without ever saying social comparison theory. YouGov published data ( here is the full data source ) that asked participants to rate their own, close-other, and far-others on several factors related to modern life (see below). In doing so, they unknowingly trigger social comparison theory, and in particular, downward social comparison. TL;DR: We know ourselves and how well we are doing compared to other people. And people are motivated to feel good about themselves. https://today.yougov.com/society/articles/48400-americans-compare-own-outlook-with-country-poll These findings smack of downward social comparison, right? Instead of having a specific target we are comparing ourself to, like a co-worker or a neighbor,...