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Showing posts from June, 2025

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Statistics hiding in plain sight: How this four-minute long interview on polling data can be used in class

Statistical literacy is important. I love examples of folks using statistical concepts without being snobby statistical gatekeepers.  For instance, see jargon-free statistical literacy that helps people make important decisions about their children's health or informs the  immigration debate .   As stats teachers, I think we are remiss if we don't talk about political polling in our classes. At least a little bit. Here is a brief, nonpartisan interview about political polling you can use in class to see whether students can identify the concepts they've learned. Here is a short  NPR i nterview o n  how to think properly about political polling. If you use the interview in class, you could ask your students to identify the statistics and research methods mentioned.  I clocked margin of error,  sampling error,  and research methodology evaluation. If using an audio interview isn't your thing, check out t his summary piece from NPR, based on the...

Rank choice voting, explained by CNN using ice cream

This one is for all of my psychometric instructors. CNN created an engaging, interactive website to explain rank choice voting using ice cream flavor preference.  It was created due to the 2025 NYC mayoral primaries, but uses ice cream instead of humans to make for a good explainer that may have a home in your classroom. https://www.cnn.com/interactive/2025/06/politics/ranked-choice-voting-explained-dg/ First, you rank order your top five favorite ice cream flavors out of a field of ten. Then, you can view all users' ranking data, and see how the distribution changes when the least popular flavor, Rocky Road, is eliminated and the rocky road voters' votes are redistributed. The vote relocation goes on and on... Finally, you get to see the winner, chocolate. Rank-choice voting is one of those concepts that is easier to explain with a bit of animation and a very simple premise. I couldn't capture it in my screenshots, but the flavor elimination and redistribution are animated...

Does unusually heavy traffic at pizzerias near the Pentagon predict global military activity?

While most of my class time is dedicated to the specifics of performing and interpreting inferential tests, basic statistical literacy and thinking are equally important lessons. Here are some of the big-picture literacy ideas I want my students to think about in my stats classes: 1. How can we use data to understand patterns to make predictions? 2. How can we separate the signal from the noise?  3. How can data actually inform real life and current events? 4. How can we repurpose existing data in a world where data is everywhere? Here is an example I JUST found that addresses all of these ideas. The  Pentagon Pizza Report is an X account that monitors Google "Popular times" data in pizzerias near the Pentagon to predict military activity.  The X account asserts that unusually high, later-than-normal foot traffic at pizzerias near the Pentagon (x) may indicate that Pentagon military staff are working late and need to grab take-out for dinner(y).  Most recently, the...