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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 bunch of pediatricians swallowed Lego heads. You can use their research to teach the basics of research methods and stats.

As a research-parent-nerd joke before Christmas, six doctors swallowed Lego heads and recorded how long it took for the Lego heads to pass. Why? As to inform parents about the lack of danger associated with your kid swallowing a tiny toy.

 I encourage you to use it as a class example because it is short, it describes its research methodology very clearly, using a within-subject design, has a couple of means, standard deviations, and even a correlation.

TL;DR:

https://dontforgetthebubbles.com/dont-forget-the-lego/

In greater detail:

Note the use of a within-subject design. They also operationalized their DV via the SHAT (Stool Hardness and Transit) scale.



*Yeah. So here is the Bristol Stool Chart mentioned in the above excerpt. Please don't click on the link if your are eating or have a sensitive stomach.

Research outcomes, including mean and standard deviations:


An example of a non-significant correlation, with the SHAT score on the y-axis and the FART score on the X-axis.:


Here is a link to the original research. And here is a link to the blogger doctors who conducted this experiment.
How to use in class:

1) Is this a sufficient sample size?
2) An example of human biology research that did sample equally from men and women.
3) In-class replication. I double dog dare you.
4) Non-significant correlation.


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