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...
This article from Nature is an excellent primer on the concerns surrounding the use of p -values as the great gate keeper of statistical significance. The article includes historical perspective on how p -values came to be so widely used as well as some discussion on solutions and alternative measures of significance. This article also provides good examples failed attempts at replication (good examples of Type I errors) and a shout out to Open Science Framework folks. Personally, I have revised my class for the fall to include more discussion of and use of effect sizes. I think this article may be a bit above an undergraduate, introduction to statistics class but it could be useful for us as instructors as well as a good reading for advanced undergraduates and graduate students.