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...
This example is a little out of my wheel house, but I'm putting it up here for those of you who teach more advanced UG stats or grad stats. I have never taught Principle Component Analysis. But Anh Le, PhD candidate at Duke, provides a detailed description of PCA in R AND does so using data that your advanced undergraduate/graduate students will enjoy: Pokemon.
So, Le downloaded data for each of the 151 Pokemon (individual stats for the strengths and weakness of each Pokemon, and provided a link so that you can download the data as well). He even included the code he used to create his PCA via R AND he does a nice job talking the reader through his process and what the findings mean.
At 37, I didn't realize how much my traditionally-aged college students love Pokemon. Pokemon came up in my undergraduate I/O class three years ago, and I was shocked by how much nostalgia my then-20 year old students felt for the franchise. I think that it is certainly experiencing a revival now and this example would really catch (haha) students' attention.
So, Le downloaded data for each of the 151 Pokemon (individual stats for the strengths and weakness of each Pokemon, and provided a link so that you can download the data as well). He even included the code he used to create his PCA via R AND he does a nice job talking the reader through his process and what the findings mean.
At 37, I didn't realize how much my traditionally-aged college students love Pokemon. Pokemon came up in my undergraduate I/O class three years ago, and I was shocked by how much nostalgia my then-20 year old students felt for the franchise. I think that it is certainly experiencing a revival now and this example would really catch (haha) students' attention.