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https://projects.fivethirtyeight.com/2024-election-forecast/
Or bayes theorem, and bayseian inference?
You might change your mind if you investigate those topics.
People get bent out of shape about 538 but it's usually because they're misinterpreting the prediction, not that the prediction is meaningless.
it does but just because nate silver calls something "statistics" doesn't necessarily mean that it is. If Donald Trump has a 20% chance of winning that means that we can hold the election 100 times and expect that he'll win approximately 20 elections and lose the other 80. Which is ridiculous because each voter is not an independent random variable.
It's not statistics because any authority says it is, it's statistics because it starts with a measure of probability (aggregated polls) and builds an interpretation on top of it. That's what statistics is. It can be good statistics or bad statistics, but that's a separate question. Incidentally, it has a pretty good track record.
If you have a criticism of Silver's model I'm curious to hear it. However, as it is I don't see a criticism in your comment. You say it's ridiculous, but it isn't. It's complicated, not ridiculous. I can't say precisely what's on your mind, but if I had to guess, it doesn't make sense to you, which is a different matter.
If you want to prove that a coin flip has a 50% chance of landing heads, a 50% chance of landing on tails, and a negligible chance of landing on its edge, you can run as many tests as you want and observe that as N approaches infinity the number of heads converges on 0.5N and the number of tails converges on 0.5N. Alternatively, you might find that the coin isn't well-balanced, in which case you've proven that the "50/50 model" was not accurate.
You can't do that with elections because each election only happens once. Even if the same two candidates are running against each other in every election, the issues at stake are different and the voterbase is different. In reality one candidate has a 100% chance of victory and the other has a 0% chance of victory but we don't know which candidate it is.
I think there’s a stronger argument that those polls were intended to suppress Trump voters into thinking they were not the majority (when in fact they were).
More than one person I've spoken to believed that when sites said things like "Hilary has a 70% chance of winning" that that was the same as getting 70% of the vote, i.e. a landslide.
I've had literal arguments with people who can't/won't understand the difference between an average and a median even when presented with 5th grade level phrasing examples.
> intended to suppress Trump voters into thinking they were not the majority (when in fact they were
Depends on what you mean by "majority". If you're just talking about Wisconsin and that specific poll, sure Trump voters ended up being in the majority, but we can't say with any certainty what that situation was in early August. Polls like that one are the best guesses we have for that particular snapshot in time.
If you're talking about an overall majority of those who ended up being actual voters, then that's also not the case, as Trump did not win a majority of votes; Clinton did. Sadly, though, popular vote majority is not how our presidential election system works.
Show your work. What evidence do you have to support that argument?
The final difference from polling in WI was 7%, other states had smaller polling errors. The fact is that 2016 was simply an extremely tight race in many states and difficult to forecast even with completely normal polling error bars.