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...
TL;DR: Birds fly away from men a bit sooner than they fly away from women. Full stop. Here is the original article, and here is a write-up from Nautilus . I love bird research. I'll get into why below. For now, let me show you how to use this example to teach three different lessons in a stats class. 1. Independent t test example with a data set The researchers shared their data. The researchers didn't analyze this data with a t test. But they did share this data visualization that looks a whole lot like one: Damn, I love the new trend of the box/violin/jitter plot. FYI: Researcher gender/the IV is labeled "gender," and how far the birds were before they flew away/the DV is labeled "FID" (flight initiation distance). Also, I love this example because the data violate the assumption of equal variance and provide a case for discussing Welch's test. 2. Conceptual example for Factorial ANOVA This example pairs well with a previous blog post featuring ...