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> but that's the whole point of confidence intervals. That would make sense if some parts of the country had errors one way, and others another way. i.e. rando
by ars 6y ago
> but that's the whole point of confidence intervals.
That would make sense if some parts of the country had errors one way, and others another way. i.e. random error.
But if every part of the country has an error, all in the same direction, then there's something larger going on.
- dragonwriter 6y ago> That would make sense if some parts of the country had errors one way, and others another way. i.e. random error. As Silver pointed out in 2016 (and why his model then gave Trump a much better chance than the NYTimes model), historically, when election outcomes differ from polls in either direction, the polling error between states is correlated, not independent. That is, it is, to all evidence, a historical fact that poll-based predictions must account for that within election cycles, there is systematic polling error, even if the direction and magnitude of that error is not consistent between cycles.
- akersten 6y ago> i.e. random error. Did they say that their confidence interval was confidence against random error? I don't think that's a requirement of a confidence interval, I think it's certainly valid to encode e.g. the chance of "shy Trump" respondents in a confidence interval.
- slg 6y agoThe results of state elections aren't independent. The problems that cause most errors are going to exist in multiple states and cause the errors to be correlated.
- thaumasiotes 6y agoBut something that causes the results everywhere to be off in the same direction isn't the kind of error you say "well, that's why you don't make point predictions" about. It's a factor that has a significant, predictable influence on the phenomenon you're studying; if it's not in your model, that means you screwed up when making the model. The whole point of the model is to account explicitly for such factors.
- esrauch 6y agoI don't think it's expecyed the errors would be random: that the polling errors are correlated and not random is something that Nate Silver talks about at length as part of the key interpretation error that others made in 2016.
- Retric 6y agoNo that says nothing about the polling just your model. 538 had an interesting page where picking a state would influence the model and change what other states where predicted to do. But I can’t seem to find it now. Figuring out the dependencies between demographics is how you come up with a useful model rather than just simulating everything independently based on raw polls numbers. Aka Michigan and Wisconsin have a lot in common where Florida is influenced by wildly different racial, demographic, and economic factors.
- ehsankia 6y agohttps://projects.fivethirtyeight.com/trump-biden-election-map/ https://projects.fivethirtyeight.com/trump-biden-election-ma...
- Retric 6y agoThanks, that’s what I was looking for. Back to my point, click Trump for Florida (which was considered a 31% chance) and the prediction looks a lot like our current map.
- kgwgk 6y agoThere is something similar for the Economist model: https://www.ricardofernholz.com/election/ https://www.ricardofernholz.com/election/
- SamBam 6y agoThat's not their method at all. They're very insistent on the fact that voting shifts or errors between states are generally highly correlated. That's exactly why their probability forecasts tend to be more conservative than other forecasts. If you see a whole lot of possible paths for a candidate, and assume the errors are random, then that candidate will almost certainly win. If you know they might be correlated, then you know that a huge number of paths may shift at once.
- deleted 6y ago[deleted]