Uhm, if it starts raining frogs or something – we are so out of here.
Anyway, he explains on his blog:
Instead, whenever we make an incorrect prediction, we are probably better off asking questions along these lines:
What, if anything, did the incorrect prediction reveal to us about the model’s flaws?
Was the model wrong for the wrong reasons? Or was it wrong for the right reasons?
What, if any, improvements should we make to the model given these results?
Don’t worry Nate – it’s the Academy – it’s so not you!