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Andrew Gelman weighs into this much more thoughtfully here: https://statmodeling.stat.columbia.edu/2020/08/14/new-fivethirtyeight-com-election-forecast/ https:/

by Tarq0n 6y ago

Andrew Gelman weighs into this much more thoughtfully here: https://statmodeling.stat.columbia.edu/2020/08/14/new-fivethirtyeight-com-election-forecast/ https://statmodeling.stat.columbia.edu/2020/08/14/new-fiveth....

disgruntledphd2 6y ago
Important to note here that Andrew Gelman is involved in the Economist model (which increases my prior that its correct, even though it shouldn't).
- wirrbel 6y ago
  well, its a well-informed meta-prior that when Gelman is involved, the model won't be absurd :-)
iaw 6y ago
> "The first thing to say is that 72% and 89% can correspond to vote forecasts and associated uncertainties that are a lot closer than you might think." I'm with Nate Silver on this one, 72% and 89% are as close as 75% and 50% in terms of being double the likelihood for a Republican win. We will likely never know which model is more accurate but given Nate Silvers history on these predictions I trust him a bit more than others.
- quico 6y ago
  > "72% and 89% are as close as 75% and 50% in terms of being double the likelihood for a Republican win." In a postscript (P.S.) Andrew Gelman clarified that the forecast distributions are close and not the probabilities of winning [0]. > "I’m not saying that 72% and 89% are close in probabilistic terms. I agree that there’s a big difference between 8-1 odds and 3-1 odds. What I’m saying is that the large difference in these probabilities arises from small differences in the forecast distributions. Changing a forecast from 0.54 +/- 0.02 to 0.53 +/- 0.025 is highly consequential to the win probability, but as uncertainty distributions they are similar and they are hard to distinguish directly. You can get much different headline probabilities from similar underlying distributions." [0]: https://statmodeling.stat.columbia.edu/2020/08/14/new-fivethirtyeight-com-election-forecast/ https://statmodeling.stat.columbia.edu/2020/08/14/new-fiveth...

by Tarq0n 6y ago

disgruntledphd2 6y ago

Important to note here that Andrew Gelman is involved in the Economist model (which increases my prior that its correct, even though it shouldn't).

wirrbel 6y ago
well, its a well-informed meta-prior that when Gelman is involved, the model won't be absurd :-)

iaw 6y ago

> "The first thing to say is that 72% and 89% can correspond to vote forecasts and associated uncertainties that are a lot closer than you might think." I'm with Nate Silver on this one, 72% and 89% are as close as 75% and 50% in terms of being double the likelihood for a Republican win. We will likely never know which model is more accurate but given Nate Silvers history on these predictions I trust him a bit more than others.

quico 6y ago
> "72% and 89% are as close as 75% and 50% in terms of being double the likelihood for a Republican win." In a postscript (P.S.) Andrew Gelman clarified that the forecast distributions are close and not the probabilities of winning [0]. > "I’m not saying that 72% and 89% are close in probabilistic terms. I agree that there’s a big difference between 8-1 odds and 3-1 odds. What I’m saying is that the large difference in these probabilities arises from small differences in the forecast distributions. Changing a forecast from 0.54 +/- 0.02 to 0.53 +/- 0.025 is highly consequential to the win probability, but as uncertainty distributions they are similar and they are hard to distinguish directly. You can get much different headline probabilities from similar underlying distributions." [0]: https://statmodeling.stat.columbia.edu/2020/08/14/new-fivethirtyeight-com-election-forecast/ https://statmodeling.stat.columbia.edu/2020/08/14/new-fiveth...