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Updated example of using baby names to illustrate bimodal distributions.

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...

A new way to goof with a y-axis.

My textbook has a feature in every chapter: Dirty Data Alerts. It warns students about ways that data can be manipulated without straight-up lying. I have one Dirty Data Alert dedicated to manipulated y-axes. Like, truncated y-axes. Because that is the way you manipulate a y-axis, right? RIGHT?! Oh, no, there is a new way to manipulate them without lying. Check out this example, pointed out by @SarahStarberry.




Here, the y-axis measures the version number. That's all. Not how good the tool is, or how often it is being used. Just the version number. Like...just wait until I come out with JessChattyTalkTalkBot 8.0 and I destroy all existing competition.

If this idea was helpful, you'll probably enjoy my textbook, Psychological Statistics for Everyone. It's basically this blog, but organized into a semester.



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