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...
Alright, kismet, coincidence, I don't know. Still, I'm noticing all of these recent and good scientific articles contain the types of statistical analyses we typically teach in Psych Stats. Like this article: Hatano, A., Ogulmus, C., Shigemasu, H., & Murayama, K. (2022). Thinking about thinking: People underestimate how enjoyable and engaging just waiting is. Journal of Experimental Psychology: General. Advance online publication. https://doi.org/10.1037/xge0001255 TL;DR: People think they won't enjoy being alone with their thoughts. BUT THEY DO, as the authors demonstrated throughout five experiments. And those experiments contained a bunch of t -tests ( and open data ). There are even a couple of ANOVAs in there. This is a fine example of how to flesh out a hypothesis using a multi-study design. And it is a round-about way of making our students (and ourselves) reflect on how we feel about boredom, alone time, and technology. It also contains some very effe...