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Showing posts with the label Wall Street Journal

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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...

DeBold & Friedman's "Battling Infectious Diseases in the 20th Century: The Impact of Vaccines"

The folks at Wall Street Journal took CDC disease data (by state, by year, courtesy of Project Tycho ) as well as information on when various vaccines were introduced to the public. And the data tells a compelling story about the importance of vaccinations. Below, the story of measles. How to use in class: -Using archival data to educate and make a point (here, vaccine efficacy) -Visualizing many data points (infections x state x year) effectively -Interactive: You can cursor over any cube to see the related data. Below, I've highlighted Pennsylvania data from 1957. -Since you can cursor over any data point to see the data, you can ask your students to pull data for use in class. -The present data were drawn from Project Tycho , a University of Pittsburgh initiative to better share public health data. This resource may be useful for your classes as well. -This data is good for Stats class, as well as Developmental, Health, Public Health, etc.