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troutman · 11-08-2016, 09:17 AM

What’s Wrong With 538?

http://www.huffingtonpost.com/entry/...b0334571e09e74

With the same information, 538 is currently predicting a 65 percent chance of a Clinton victory, while HuffPost’s Natalie Jackson and Adam Hooper are projecting a 98 percent chance,[1] and Sam Wang at Princeton Electoral Consortium is predicting a >99 percent chance.[2] What gives?

Underlying this is an overly complex and opaque set of assumptions that are probably too smart for their own good.

The mantra for model building has always been “garbage in, garbage out.” You can have the most intricate set of assumptions, but if your model is spitting out unrealistic results, there’s something wrong with your model.

538’s probability of a Clinton or Trump victory relies on the results of at least 20,000 model runs each time a new poll (or set of polls) comes in.[5] To get their probabilities of victory for each candidate, they sum up the number of times that candidate got 270 or more electoral votes on each run, much like Jackson and Hooper at HuffPost or Sam Wang at PEC.

It’s great to build a complex model and load it with empirical data like polls, economic reports and presidential approval ratings. But if the output of that model is implausible, it’s time to go back to the drawing board.

11-08-2016, 09:17 AM	#31
troutman Unfrozen Caveman Lawyer Join Date: Oct 2002 Location: Crowsnest Pass Exp:	What’s Wrong With 538? http://www.huffingtonpost.com/entry/...b0334571e09e74 With the same information, 538 is currently predicting a 65 percent chance of a Clinton victory, while HuffPost’s Natalie Jackson and Adam Hooper are projecting a 98 percent chance,[1] and Sam Wang at Princeton Electoral Consortium is predicting a >99 percent chance.[2] What gives? Underlying this is an overly complex and opaque set of assumptions that are probably too smart for their own good. The mantra for model building has always been “garbage in, garbage out.” You can have the most intricate set of assumptions, but if your model is spitting out unrealistic results, there’s something wrong with your model. 538’s probability of a Clinton or Trump victory relies on the results of at least 20,000 model runs each time a new poll (or set of polls) comes in.[5] To get their probabilities of victory for each candidate, they sum up the number of times that candidate got 270 or more electoral votes on each run, much like Jackson and Hooper at HuffPost or Sam Wang at PEC. It’s great to build a complex model and load it with empirical data like polls, economic reports and presidential approval ratings. But if the output of that model is implausible, it’s time to go back to the drawing board.