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...
Now and again, I run across a news article or psychological question that is so big that it bleeds out of straight statistics and requires a thorough understanding of the research methodology that guides statistical choices. When that happens, I email my buddy and fellow W.W. Norton author, Beth Morling, and we write a joint blog post. Recently, I emailed her because research on using psychedelics to treat many different mental disorders has been in the news. President Trump fast-tracked this research, and the Journal of the American Medical Association recently published a big meta-analysis on the topic. Psychedelic research has always interested me because of psychology, but it has always amused me because of how you run a proper double-blind research study if your experimental participants KNOW that they are hallucinating and your control group participants know they are not? This broader question offers a few great discussion options for you and y...