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 is a funny, small example for anyone who discusses managing missing data in a database. This example also touches on what can go wrong when using someone else's data or you merge datasets. So, this piece of information made the rounds in August: This isn't a lie. The voter rolls in Racine had over 20,000 voters with the same phone number. Which led to measured responses from voting rights experts on Twitter. Redhibiscus was so close to the truth! I assure you, if you have ever dealt with complicated databases, especially those that have been merged and go back decades, it isn't unusual to fill in missing data with a specific number repeatedly. Here is a fact check from the A.P. : https://apnews.com/article/fact-checking-612360682016?utm_source=Twitter&utm_campaign=SocialFlow&utm_medium=APFactCheck This isn't a big lesson for a statistics class, but it is a funny and horrifying example of how database management practices fueled a conspiracy theory. It is al...