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...
Jennifer Raff is a geneticist, professor, and enthusiastic blogger . She created a helpful guide for how non-scientists (like our students) can best approach and make sense of research articles. The original article is very detailed and explains how to make sense of experts. Personally, I appreciate that this guide is born out of trying to debate non-scientists about research. She wants everyone to benefit from science and make informed decisions based on research. I think that is great. I think this would be an excellent way to introduce your undergraduates to research articles in the classroom. I especially appreciated this summary of her steps (see below). This could be turned into a worksheet with ease. Note: I still think your students should chew on the full article before they are ready to answer these eleven questions. http://blogs.lse.ac.uk/impactofsocialsciences/2016/05/09/how-to-read-and-understand-a-scientific-paper-a-guide-for-non-scientists/#author ...