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...
State Farm, a prominent American insurance provider, shared data that ranked American states based on the number of animal-related (mostly deer) car accident claims filed per state . I blogged about this data previously , and I am returning to it now as part of my semi-regular Discussion Board Ideas series on this blog. I have been using this prompt in my online stats class in NW PA for about a year now. I'm going to share some of that success here. Note: PA is #4 for deer-related car accident claims, so this data resonates with my students. I use this for the fifth of seven weeks in my online class, so the students are comfortable with the class format and one another by then. Here is the exact prompt I use: I have a weird question for you: How do you think Pennsylvania ranks when it comes to the number of car accident insurance claims involving colliding with animals? Yes, I am on my soapbox about safe night-time driving in PA. Once you have your guess, check against...