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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...

Mathisfun.com's Least Squared Error calculator

Mathisfun.com bills this as a Least Squared Error calculator, but I don't think it is a calculator. I think it is a nice visual aid that demonstrates how the regression line/equation change as your data changes.

The static photo below doesn't do this interactive website justice. You can drag and drop any of the dots on the scatter plot and watch as the regression line and regression line equation are recalculated to best predict Y based on X.


It doesn't explicitly show the math going on behind the scenes, but it is a nice compliment to your LSE lecture.





https://www.mathsisfun.com/data/least-squares-calculator.html

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