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...
Prior to the 2012 presidential election, Pennsylvania attempted to enact one of the toughest voter ID laws in the nation. This law has been kicked up to the courts to examine its legality. One reason that so many people protested the law was because it would make it more difficult for the elderly and the poor to vote (as it would be more difficult for them to obtain the ID required). Here is an NPR story that gives a bit of background on the law and the case in court. Also, for giggles and grins, here is Jon Stewart's more amusing explanation of the law and why it was struck down prior to the election, including video footage of a PA legislature flat-out stating that the Voter ID law would allow Romney to win the 2012 election. In order to support/raise questions about the impact of the law on the ability to vote, statisticians have been brought in on both sides in order to estimate exactly how disenfranchising this law will be. Essentially, the debate in court centers a...