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...
http://io9.com/i-fooled-millions-into-thinking-chocolate-helps-weight-1707251800 This story demonstrates how easy it is to do crap science, get it published in a pay-to-play journal, and market your research (to a global audience). Within this story, there are some good examples of Type I error, p -hacking, sensationalist science reporting, and, frankly, our obsession with weight and fitness and easy fixes—also, chocolate. Here is the original story, as told to io9.com by the perpetrator of this very conscientious fraud, John Bohannon . Bohannon ran this con to expose just how open to corruption and manipulation the whole research publication process can be ( BioMed Central scandal , for another example), especially when it just the kind of research that is bound to get a lot of media attention ( LaCour scandal , for another example). Bohannon set out to "demonstrate" that dark chocolate can contribute to weight loss. He ran an actual study ( n = 26). He went on a ...