I intended for this to be a post about the singer vocabulary. It is still that, but it is also a post about using GenAI to grab data from an image. I mean, you can use Excel to do the same thing, but GenAI is a lot easier. Here we go. It starts with the Word Tips website, which helps you solve your crossword puzzles and Wordle. This website also has a blog dedicated to words. One such blog post explored which singers have the largest vocabularies, as measured by the number of  unique words in their lyrics. Their blog post compared music legends to newer talent. There are a ton of fun data visualizations on the website; go check it out. Since I teach college students, I decided to concentrate on the musicians my students listen to: In and of itself, this image serves as an example of bar graphs, good data visualization, and proper use of "buckets". However, I figured we could find a way to use the raw data in class. Create your own data visualization, create your own buckets....

Look at how Dima Yarovinsky turned the Terms and Conditions documents for several social media platforms into foreboding and beautiful art/bar graphs illustrating how much we sign away without reading. Note: He even uses the X axis to describe the length of and reading time for each T&C statement!  I think data is beautiful. This example does a good job of showing the beauty and impact of good data visualizations to my students. This isn't a huge example to use in class, but I will use it next time I discuss bar graphs. For more from the artist, in his own words, visit his webpage .  For a thought review of this art, see this article by Emma Taggart .

They are bar graphs. And they are funny.

This is a fun question perfect for that first or second chapter of every intro stats text. The part with data distributions. And it works for either the 1) beginning of the Fall semester and, therefore, football season or 2) the beginning of the Spring semester and, therefore, the lead-up to the Superbowl. Anyway,  Ben Jones   tweeted a few bar chart distributions that illustrate different descriptive statistics for NFL players. https://twitter.com/DataRemixed/status/1022553248375304193  He, kindly, provided the answers to his quiz. How to use it in class: 1) Bar graphs! 2) Data distributions and asking your students to logic their way through the correct answers...it makes sense that the data is skewed young. Also, it might surprise students that very high earners in the NFL are outliers among their peers. 3) Distribution shapes: Bimodal because of linebackers. Skewed because NFL players run young and have short careers. Normal data for height because even...

Here are a bunch of Statsy GIFs. I did not create any of these but I love them all. https://www.instagram.com/linski101/ https://www.instagram.com/linski101/ https://www.instagram.com/linski101/ CI for regression lines: https://twitter.com/ClausWilke/status/1034492581588156416