[RivieraKid]

I'm surprised that a lot of people almost worship the 538 model, when there is a better model with more competent people behind it. Economist is also more open about how their model works and it's open-source. After reading the methodology I was pretty impressed.

Edit: Why am I being downvoted?

[abnry]

While numerically literate, I don't understand the details of the 538 or economist models. What I do know is that 538's model has had a great track record. It gave Trump one of the highest chances of winning in 2016. It did very well in prior elections. And both models are essentially predicting the same results: ~10% chance of Trump winning.

[ceilingcorner]

How is being slightly less wrong than everyone else "having a great track record"? Serious question. Because I find it hard to take any of them seriously after the debacle that was 2016.

[gamblor956]

They were generally correct with their prediction except in 3 states where nobody had been doing detailed polling because the pollsters didn't think it would matter.

It simply wouldn't have been possible for the models to be more accurate with the data they had. As they say, bad data in, bad data out.

That's why this time around the pollsters made sure to be more thorough in their polling.

[ceilingcorner]

> That's why this time around the pollsters made sure to be more thorough in their polling.

"This time is different."

I've heard that enough times to be highly skeptical. I'm also deeply skeptical of the notion that polling is even remotely correlated to actual results. Cultural and historical trends play a drastically higher role and are almost always left out.

[chki]

> I'm also deeply skeptical of the notion that polling is even remotely correlated to actual results.

But it has been strongly correlated to the results in basically all elections so far in all democracies on the planet. Taking 2016 as an example there has been a very strong correlation between polling and the results. The national polling averages were only 3 points off from the actual result. If that's not correlated I don't know what is.

[ceilingcorner]

Polarization and the unacceptability of publicly saying "I voted for X" also didn't really exist prior to 2016. The fear of getting doxxed, combined with a record low level of trust in institutions and the media, leads to skepticism toward answering polls truthfully, IMO.

[jimmygrapes]

The shy Tory factor[0] is likely to be even stronger this year than in 2016 when it comes to polls. After 4+ years of being harangued and called every name in the book by the vast majority of national culture (movies, music, TV, news, social media, news-entertainment), along with increasingly hostile projects such as https://donaldtrump.watch/ I imagine less of his more subdued supporters are going to be honest with pollsters.

[0]: https://en.wikipedia.org/wiki/Shy_Tory_factor

[noirbot]

But wouldn't that mostly be concentrated in places/areas where their votes aren't likely to matter? Having just driven through the US South in the last month, I can confidently tell you people are not in any way shy about their support for Trump. I saw more Trump signs and flags than I saw US flags.

It's also likely this works in both directions - if you support Biden, I bet you don't have a yard sign for it if you live in Mississippi.

By construction, the effect is strongest the more you're not in the majority, which also means your unspoken support is more likely to not matter on the actual outcomes of the election.

[JJzD]

If you're right, the support for Trump should be higher in polls where people talk through a phone menu or the internet, compared to live interviews.

Newsflash, they aren't, so your hypothesis must be they're too shy to admit their Trump support to a machine?

Everybody is just fighting the last war where Trump suddenly won for a couple of reasons. So, the Dems are scared they are missing something, and the Reps are going "Haha, who cares about modelling".

Will, the forecasts be perfect? Nope. But is the margin rather large, but not unsurmountable? Yes it is. Are the mistakes from last time repaired? Yes, they take care of uneducated whites. Is there evidence Trump has found a new source of voter support? I haven't seen it.

[ceilingcorner]

Yep. I see this everywhere, both online and in person.

[gamblor956]

Anecdotal, but I have never met a Trump supporter that was shy about who they were voting for, this year or in 2016.

If anything, Trump supporters have been extremely vocal about who they were supporting, to the extent that they frequently violate social norms and try to takeover events and gatherings to make their political affiliations known, like this week with Among Us.

[massysett]

Saying that the ultimate outcome had a 1 in 4 chance is not wrong, slightly wrong, or less wrong. If the weatherman says there's a 1 in 4 chance of rain, and it rains, he wasn't wrong.

[swsieber]

To take it a step further, if that was the forecast 4 days in a row, you would expect it to rain one of those days.

[warrenq]

Not necessarily.

There is a 0.750.750.75*0.75 or a 31% chance of no rain at all

[swsieber]

I'm not saying it's certain, but it's what I'd expect. It raining on one day out of 4 is the most common case.

[ceilingcorner]

No, but it means that the weatherman isn't particularly effective at forecasting the weather.

[bart_spoon]

No it doesn’t, and this is a fundamental misunderstanding of how probabilistic forecasting works. If it rains 9 out of 10 times a weatherman says there is a 30% chance of rain, they are a bad weatherman, but they aren’t much worse than if it rained 0 out of 10 times they predicted a 30% chance of rain. A weatherman accurately assessing the probability of the weather forecast would see it rain around 3 out of 10 days they say there is a 30% chance of rain.

[noirbot]

Only if they say that every day, and it rains every day. If the most likely outcome happened every time, then the model is likely wrong/under-confident. The prediction is never going to be 100% accurate until the event is happening/has happened. Up until then, there's always a chance you're wrong or something can change. Being wrong once isn't necessarily a sign that the whole system is messed up.

[khuey]

This is a fundamental misunderstanding of probability. Low probability events do happen, and it doesn't inherently mean the estimated probability was wrong.

[ceilingcorner]

I am criticizing their labeling of Trump's win as low probability.

[khuey]

"He won" is not sufficient evidence upon which to do that.

[ceilingcorner]

Nowhere did I say it is. I simply think that, if one were following the right information, his win was not as unexpected as the coastal media presented it as being.

Personally I would have put it about 60-40 Hillary-Trump.

[pjanoman]

At the end of the 2016 election, Donald Trump had a predicted 1/4 chance of winning the presidency. Does this seem like a massive debacle that Trump won under these conditions? Not to me.

https://projects.fivethirtyeight.com/2016-election-forecast/

[abnry]

They said Trump had a 1 in 4 chance. That's very high. NYT had something like 1 in 20 chance for Trump.

[ceilingcorner]

That doesn't really answer my question. It only indicates that they were slightly less wrong than every other media source, not that they have a good model.

If I had a laptop that only worked 1/4th of the time, rather than 1/20th of the time, would that make it a reliable laptop? I don't think so.

[pedrosorio]

If they were wrong, but “less wrong” than all others, you should pick their model (unless you have an oracle, because the alternative - flipping a coin or “relying on your intuition” is rarely better).

Also, it doesnt make sense to look at a single prediction to evaluate a model.

Out of all the predictions they have made (did you look at individual state predictions?), how many were correct (and how confident were they?) - how many were wrong (and how close to 50% were they?).

That is how you evaluate a model (aka cross entropy)

[delecti]

It's not "wrong" to predict a low chance for something that eventually happens. Unlikely events can happen.

[ceilingcorner]

That isn't the criticism. The criticism is the appellation of it being "unlikely."

For example: anyone paying attention to the Rust Belt ±1980-2016 would have dramatically upped Trump's chances in Pennsylvania and Michigan. FiveThirtyEight had Hillary with 70%+ chance of winning both, which to me, shows a deep ignorance of actual cultural factors.

[tracer4201]

It seems like you are conflating probabilities with absolute certainties. If I had a 1:10 probability of winning the lottery, I would probably take it. If I had a 1:20 probability of getting injured if I leave my house today, I’d stay home. If I did get out but didn’t get injured doesn’t mean the model was wrong.

[shajznnckfke]

If you have a die that rolls a one 1/6 of the time, do you consider the die wrong?

[ceilingcorner]

No, but I don't consider it useful toward predicting the outcome, which is of course what this is all about.

[Tyr42]

If I tell you you're not likely to get two heads in a row, and you do, does that make me un-reliable?

It's unfortunate we can't just run the election again a few times, and actually find the rate at which Trump is elected given the polls.

And it's not empty signalling if 538 assigned Trump a higher chance of winning; they were pretty much the only ones saying he has a chance. That is why people think the models are useful.

[abnry]

If everyone was wrong, it is reasonable to believe a low probability event occurred. However, given the extent to which people predicted a Trump loss (say 1 in 20), which is significantly rarer, given that the event occurred it suggests the model that predicted a Trump win with the greatest probability to likely be a more accurate model.