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...
Create an account with Pew Research, and you can download some of their data sets, including a) syntax files, b) detailed methodology, and c) codebook, including detailed screenshots of what the survey felt like to participants. I think there are three ways to use this in class: -Show your students what proper data documentation looks like -Get some data, run some analyses -Get some data, look up Pew's reports based on the data, see if you can replicate the findings. How to Properly Document Your Research Process. Pew documents the hell out of these data sets. Included are: Syntax files: Methodology: Surveys, featuring the questions but also screenshots of the user experience: Get some data, run some analyses. MY FIRST EVER FACTOR ANALYSIS EXAMPLE, y'all. Per the methodology documentation, Pew creates its own scales. Within this data set (American Trends Panel Wave 34), they use several scales to measuring attitudes about medical treatments. ...