Forecasting uncertainty in practice: Snowperbole

Example of snow forecast communicating levels of uncertainty; image from the Capital Weather Gang

Because making accurate predictions is extremely difficult, we can dramatically improve both the accuracy of forecasts and enable effective communication about the forecast by embracing the uncertainty involved in the forecast. This allows decision-makers to both use the information available

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The cone of uncertainty

One of the elements that makes prediction difficult is uncertainty. In one of the chapters of Donald Shoup’s High Cost of Free Parking (adapted for Access here), Professor Shoup poses the question:

HOW FAR IS IT from San Diego to San Francisco? An estimate of 632.125 miles is precise—but not accurate. An estimate of somewhere

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Prediction is hard – so why do we make key decisions based on bad information?

Comparison of USDOT predictions for Vehicle Miles Traveled, compared to actual values. Chart from SSTI.

Back in December, David Levinson put up a wonderful post with graphical representations looking to match predictions to reality. The results aren’t good for the predictors. Lots of official forecasts call for increased vehicle travel, while many places have

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