Cortically Magnified

It has become very obvious that extreme weather is a clear and present danger. Globally, 2023 was the hottest year ever recorded, and some scientists are predicting that 2024 will be humanity’s first year beyond the 1.5°C threshold above pre-industrial average temperature. On a personal level, just last week, my house in Melbourne was without power for more than 8 hours, due to a large-scale blackout in Victoria caused by strong winds and high temperatures.

The Simpson’s Paradox is one of the most well-known paradoxes in statistics. A quick google will find plenty of blog posts (many from the data science community) about this puzzling phenomenon. It is clearly a topic of real-world significance. There seem to be some important lessons that we are supposed to learn from it. But what are those lessons? Is it nothing more than a cautionary tale about how easy it is for data analyses to go wrong?

A colleague recommended a book called “Computer Age Statistical Inference” by Efron & Hastie. I love the organization. Part I - classical stuff. Part II - Early computer-age methods. Part III - 21st century topics. That’s exactly the type of textbooks that we need.