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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...

Kristopher Magnusson's "Understanding the t-distribution and its normal approximation"

Once again, Kristopher Magnusson has combined is computer programming and statistical knowledge to help illustrate statistical concepts. His latest interactive tool allows students to view the t-curve for different degrees for freedom. Additionally, students can view error rates associated with different degrees of freedom.

Note that the critical region is one-tailed with alpha set at .05. If you cursor around the critical region, you can set the alpha to .025 to better illustrate a two-tailed test (in terms of the critical region at which we declare significance). 

Error rates when n < 30

Error rates when n > 30

This isn't the first time Kristopher's interactive tools have been featured on this blog! He has also created websites dedicated to explaining effect size, correlation, and other statistical concepts.

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