Predictions are only as good as the regularity of the event

Weather prediction is data. This makes weather data-related stories and examples highly relatable.

The Washington Post published an interactive article that lets you see how accurate weather predictions are for a given city in the United States. This means that we, stats instructors, can use this page to provide a geographically-personalized lesson on weather prediction, the limitations of data, and why predictions about the future are only as good as the consistency of the past.

I also like this example because it isn't terribly mathy and encourages statistical literacy. 

Kommenda and Stevens, writing for the Washington Post, recently shared a story on the accuracy of weather predictions based on time away from the target day. Here, the DV is prediction accuracy, operationalized using the difference between predicted and actual high temperature. You could always ask your students how they would operationalize weather...or maybe some weather matters more than others? Folks in Erie, PA, aren't as concerned about temperature differences as we are about inches of snow or the severity of windstorms created by Lake Erie. 

The article includes reasons for these patterns, which can get you and your students talking about causality:

In addition to the examples above, I think there is a faint pattern in the East that shows that the Appalacian Mountains may goof with either predictions? That tracks with my lived experiences, growing up outside of Altoona, PA.

ANYWAY.

Another fun feature is that you can look up your town (well, I guess this is only fun if you live in America). But, it is NOAA data, so US data. ANYWAY: My intuition was backed up: Erie, PA doesn't have the best predictive powers. Especially in the winter. My understanding is that this is due to Lake Erie.

As statistical tools get better, and data collection occurs on an ever bigger scale using more devices, overall predictions are getting better:

This graph illustrates that statistics is not static; it is always changing, and it has a practical effect on the lives of all people as weather predictions become more accurate.