Tag Archives: Behrens-Fisher

Episode 4: Weather Talk

weather

We know that The Weather is the most basic, most mundane small talk topic in, you know, the world.  We understand that The Weather is just boring to discuss.

Except when it isn’t.

Join us in this episode as we discuss the fascinating, and varied, uses of math in weather predictions, from model-building to handling competing forecasts. We speak with Hannah Christensen, a postdoctoral researcher in the Physics Department of Oxford University, whose 2015 Guardian article, Banking on Better Forecasts: The New Maths of Weather Prediction, outlines how forecasters use probabilistic models to minimize, or at least better explain, the “chance” in next week’s chance of rain.  We also have a conversation with Frank D’Amico, a statistician at Duquesne University, who explains the conditions under which the simple act of comparing two bell curves turns into one of the greatest unsolved puzzles in statistics, the Behrens-Fisher problem.

Turns out, The Weather isn’t so boring, after all.  To hear why, listen in to our conversation in Episode 4.  We promise: It’s not just small talk.

Music from LOWERCASE n.

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