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...
I love data-informed opinions and arguments. So, I was fascinated when NPR told me that some academics quietly take side gigs in which they use data to help tobacco companies. Specifically, tobacco companies argue that, over time, people have become more and more aware of the risks associated with smoking. As such, Big Tobacco argues that they should not be held responsible for the harm caused by smoking. From NPR: I went down the rabbit hole to find the original data and more information on Gallups position, and this is what I found: https://news.gallup.com/poll/1717/tobacco-smoking.aspx So, while American's had heard about the potential connection between cancer and smoking, not everyone believed that this was true (41%), and many people weren't sure about the link (29%). How to use in class: -Data used in court. -Data is used by historians. More here: http://www.stat.columbia.edu/~gelman/stuff_for_blog/Ethics-of-Consulting-for-the-Tobacco-Industry.p...