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...
Here is a quick RM review I created for my Psych Stats students. We were preparing for the first exam, which covered the very basics of research methodology, including IVs and DVs. We also talk about data visualizations and how they can be used to quickly convey information. California is dealing with an energy crisis and a heatwave. California tried a relatively inexpensive intervention to reduce the likelihood of overwhelming the energy grid: Sending out text messages during extremely high energy usage. See: https://www.bloomberg.com/news/articles/2022-09-07/a-text-alert-may-have-saved-california-from-power-blackouts And what happened? People reduced their electric usage. Source: https://www.bloomberg.com/news/articles/2022-09-07/a-text-alert-may-have-saved-california-from-power-blackouts For the class review, I asked my students to think of the emergency alerts they receive from their university via our campus safety app. I challenged them to think of a c...