Many thanks to Dr. Sara Appleby for sharing this data with me!! I really enjoy silly data, like this  one from Jayson Jenks, writing for  The Athletic,  which shows how many Uncrustables each team eats per  week. Well, data from the teams that elected to participate and/or didn't make their own PB and Js. The whole article is fun, so give it a read. It makes sense that hungry athletes would go for a quick, calorie-dense, nostalgic snack containing protein.  Here is the data visualization:  Damn, Denver.  I entered this data into a spreadsheet for all of us. Spoiler alert: The number of Uncrustables eaten per week does not vary by league (independent t -test example), and the number of wins in 2023 does not correlate with the number of Uncrustables eaten per week in 2023 (correlation/regression example). Also, for my own curiosity, I re-ran the data after deleting Denver, and it wasn't enough of a difference to achieve significance.  

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...