At SciPy 2023 I presented a talk called “Taming Black Swans: Long-tailed distributions in the natural and engineered world“. Here’s the abstract:

Long-tailed distributions are common in natural and engineered systems; as a result, we encounter extreme values more often than we would expect from a short-tailed distribution. If we are not prepared for these “black swans”, they can be disastrous.

But we have statistical tools for identifying long-tailed distributions, estimating their parameters, and making better predictions about rare events.

In this talk, I present evidence of long-tailed distributions in a variety of datasets — including earthquakes, asteroids, and stock market crashes — discuss statistical methods for dealing with them, and show implementations using scientific Python libraries.

The video from the talk is on YouTube now:

Here are the slides, which have links to the resources I mentioned.

Don’t tell anyone, but this talk is part of my stealth book tour!

• It started in 2019, when I presented a talk at PyData NYC based on Chapter 2: Relay Races and Revolving Doors.
• In 2022, I presented another talk at PyData NYC, based on Chapter 12: Chasing the Overton Window.
• In May I presented a talk at ODSC East based on Chapter 7: Causation, Collision, and Confusion.
• And this talk is based on Chapter 8: The Long Tail of Disaster.

If things go according to plan, I’ll present Chapter 1 at a book event at the Needham Public Library on December 7.

More chapters coming soon!