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...
McFadden's "Frances Oldham Kelsey, F.D.A. Stickler Who Saved U.S. Babies From Thalidomide, Dies at 101"
This obituary for Dr. Frances Oldham Kelsey that tells an important story about research ethics, pharmaceutical industries, and the importance of government oversight in the drug creation process (.pdf here).
Dr. Kelsey was one of the first officials in the United States to notice (via data!) and raise concerns about thalidomide, the now infamous anti-nausea drug that causes terrible birth defects when administered to pregnant women. The drug was already being widely used throughout Europe, Canada, and the Middle East to treat morning sickness, but Dr. Kelsey refused to approve the drug for widespread use in the US (despite persistent efforts of Big Pharm to push the drug into the US market). Time proved Dr. Oldham Kelsey correct (clinical trials in the US went very poorly), and her persistence, data analysis, and ethics helped to limit the negative effects of the drug on American children.
I like this example because it shows that government safeguards can work and that we need data in order to provide evidence to protect public health. Also, the hero of this story is a woman...with her doctorate...in the 1960s...which makes her efforts all the more impressive.
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| Dr. Kelsey, receiving the President's Award for Distinguished Federal Civilian Service (highest honor given to federal employees) |
Dr. Kelsey was one of the first officials in the United States to notice (via data!) and raise concerns about thalidomide, the now infamous anti-nausea drug that causes terrible birth defects when administered to pregnant women. The drug was already being widely used throughout Europe, Canada, and the Middle East to treat morning sickness, but Dr. Kelsey refused to approve the drug for widespread use in the US (despite persistent efforts of Big Pharm to push the drug into the US market). Time proved Dr. Oldham Kelsey correct (clinical trials in the US went very poorly), and her persistence, data analysis, and ethics helped to limit the negative effects of the drug on American children.
I like this example because it shows that government safeguards can work and that we need data in order to provide evidence to protect public health. Also, the hero of this story is a woman...with her doctorate...in the 1960s...which makes her efforts all the more impressive.