He "beat the odds" because most models were incorrect. They have been corrected. Are the models wrong again? Maybe, but it would need to be in a totally different way, and by a much larger margin than in 2016.
Hispanic vote numbers are wrong this cycle (too high of support for Biden in the models). Might not matter, I'm still expecting a Biden victory.
This sounds like something a soviet comission would declare after an accident. What went wrong and how was it corrected? You needn't know, it has been corrected.
Opining without doing any research is lazy and undermines good conversation. Your exchange with GP literally amounts to a "uh huh / nuh uh".
Name-calling, FWIW, is even less productive.
>> you needn't know, it was corrected
There were long reports on what went wrong (and what didn't) in 2016 polling.
For example, https://www.aapor.org/Education-Resources/Reports/An-Evaluat...
More importantly, there are explanations from pollsters about what they changed and they speak openly about remaining possible sources of uncertainty/error. See e.g. the quotes in this article: https://www.newsweek.com/how-pollsters-changed-their-game-af...
All of this is a quick google search away, and anyone who has actually paid attention to polling knows exactly how polling has changed in the past 4 years. It's literally impossible to read anything on this topic without knowing that polling firms openly talk about methodology changes. Therefore, your original comment was either intentionally misleading or profoundly uninformed.
NB: You can absolutely agree or disagree with their methodological choices, especially around "shy Trump effect" and whether Trafalgar-like "what do your neighbors think?" questions make sense.
But even if you disagree with their choices, _it's plainly untrue to say their attitude is "you needn't know". To the contrary, they're quite open about how their polling methodology has changed._
Are you willing to defend with evidence and reason your initial claim that pollsters haven't explained what they have/haven't done to try and correct polling methodology? Or are we just going to name-call like we're 12 year olds on a playground/irrelevant partisan zombies in the internet comment section?
Based on what are you saying this?
I refuse to believe relativity until Einstein gives me a personal audience. Gravity, for that matter, is wholly unbelievable unless Galileo will sit with me under a tree. This is how the scientific method works: you must personally meet the scientist in order to believe anything they say. :)
But seriously, I have no idea what point you're trying to make here. I've met geneticists but have never met a virologist. Does that mean I should have more belief in the existence of DNA than in the germ theory?
Running the actual experiment requires a real election. Polls were more accurate in 2018 than in 2016, but we haven't yet had a presidential election with updated methodology. And presidential elections are different from midterms.
Again, of course you can construct a polling methodology that gives a pre-determined desired result (including the exact results of any particular election). This is called fitting a parameter.
And, again, the fact that you can tweak the weights on 2016 polling data so that the polls predict the right result is literally just a mathematical fact. And an uninteresting fact at that.
But you can't run a real experiment to test the the effectiveness of a new sampling method without actually holding an election.
I'm not even making any particular claim about the accuracy of polls this year.
I'm literally just saying that the fact that you can fit a model to give a historically correct answer on historical data that used one sampling method doesn't necessarily tell you the accuracy of a forecast that uses a different sampling method.
TBH, if we were talking about an advertising campaign, this wouldn't even need to be said out loud (or, if it did, the team member who didn't understand would be PIP'd ASAP).
> but the polls are not conducted by district but are conducted by "statewide random polling" which is about as useful in a country with an electoral system such as the US as the popular vote count. That is, not at all.
That's just false. Nearly every state allocates its electoral college votes based upon the state's popular vote. Hypothetical 100% accurate polling of the state's popular vote will absolutely tell you who gets the EC votes in at least 48 states. No?
Re: the distribution of the popular vote within each state, high-quality state polls DO weight for geography. But, again, you don't need to know
Also, the last person ANYONE should be listening to is 538/Nate Silver. People need to remember that before he was in politics, he used to be in sports betting but because his "models" were so terrible, he got pushed out of the industry. Nothings changed and he is still as wrong as ever.
If HN wants some high quality punditry, look at People's Pundit and their shows, Barnes Law (20 year election better wbo has never failed to make a profit in a cycle), and Cotto Gotfried. Stay away from the Nate Silvers and the Nate Cohns, terrible data and terrible forecasts.
That website's subtitle is "forecasting presidential elections since 1912". What does that even mean? Is Helmut 120+ years old? Or does he mean "fitting" instead of "forecasting"?
BTW: Helmut's model was jut wrong in 2016. Its prediction -- the actual statistical forecast the model actually made -- was that Trump had an 87%-chance of winning the popular vote. That was its forecast -- of the popular vote, not of the electoral college. Its electoral college forecast was then conditional on its popular vote forecast. The actual core quantitative prediction the model made was in fact wrong. Literally, the primary model got the right result by accident.
Of course, Helmut retroactively claims that because he got the EC right it doesn't matter. Which would be somewhat reasonable if:
a) that's how the model actually worked (it isn't -- the model's core prediction was about the popular vote and it was wrong), or
b) he didn't make exactly the OPPOSITE corrective about his model's performance whenever he talks about 2000, where he always stresses that it at least got the popular vote right even though it got the EC wrong.
Why does this matter?
First, Helmut's model isn't as good as he claims it is even on historical data. He moves the goalposts from year to year.
Second, Models that get the right answer for the wrong reason are usually over-fit to historical data. They should be taken with a grain of salt in years where their core feature set might behave differently that in previous years. (E.g., a year in which the model's main predictive feature -- primary results -- were cut short due to a 1-in-100-year pandemic).
Anyways, there are a lot of other contrarian/first-principles models that back-test well and predict a (D) win. Of course, no one cares about those this year. But they might next time around if the polling-based methodologies predict an (R) win.
FWIW, I tend to agree that the polling aggregation models are "meh" and should have way more uncertainty than they currently do. Mostly because a) I think turnout is much more correlated between swing states than those models typically assume and b) I don't think aggregating polls is actually all that useful.
Basically, everyone in election polling is making educated guesses and everyone in election polling over-sells their certainty.
Also, re: betting markets. Through a combination of bets on state-level results, you can construct positions that pay out if EITHER Democrats win the popular vote OR Republicans win the electoral college. The odds of Republicans winning the popular vote but losing the college are basically zero. I guess my point is just that there are lots of idiots betting on elections and you can trivially construct (small) sure-to-win positions.