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The Unstoppable Pop of Taylor Swift: Data visualizations, variable operationalization, and DATA DATA DATA

  The unstoppable pop of Taylor Swift (reuters.com) Here are some ideas for using this to teach statistics: Data visualizations and visualization guides: With cats, y'all. And the Taylor Swift handwriting font. I love the whole vibe of this as well as how they explain their data visualizations. Operationalizing things: The page describes three Spotify metrics for music: Acousticness, danceability, and emotion. The data visualization contains a numeric value for each metric and a description of the metric's meaning. DATA!: Okay. This is an excellent example of things already. And it is delightful. Then I thought, "Oh, wouldn't it be fun if this was in spreadsheet form!" (I think that A LOT, friends). But, as I write a book and my syllabi, I don't have time for that,  BUT A REDDITOR DID HAVE TIME FOR THAT . Dr. Doon created a spreadsheet with 18 columns of Spotify data for each son. It doesn't include the Midnights data but is still a fantastic amount of dat...

America's worse drivers, according to Consumer Affairs.

Consumer Affairs released a list of America's best and worst drivers . It is a short article but contains many good stats nuggets. 1. Ratio and ordinal versions of the same data. 2. Where did the ratio data come from? Take a look at the Methodology. 3.  Here is the data for the twenty most terrible driver s. It includes the nominal/ratio data I shared above and the top four bullet points from the image above. 4. Where did they find their data? Lucky for us, they cite their data. Which is good form, right? But also, it is an example of how much hecking data is out there. 

Mark Rober's 14 minute long primer on machine learning

I'm a fan of former NASA engineer and current YouTuber/science comm pro  Mark Rober . He meets the sweet spot of containing YouTube content that is safe for kids but also engaging for adults. You may know him for creating obstacle courses for squirrels in his backyard and holding the world record for the tallest elephant toothpaste explosion .  Recently, I discovered that he made a stats-adjacent video  explaining machine learning by studying baseball signals and creating a way to de-code baseball signals . Anyway, if you touch on your topics in your classes, this is a great, quick explainer. It is well-edited, well-produced, and has captioning. You don't need to be a baseball fan to follow this example.