Those are the raw data from polls (an estimate of the popular vote), not the predictions from them ("who will win" - which is what the original commenter refers to).
Fivethirtyeight had Clinton at 88% less than a month out from election day: https://projects.fivethirtyeight.com/2016-election-forecast/...
I.e. a couple weeks before James Comey announced a reopening of the investigation into the email issue?
I agree that 538 was likely over-interpreting their data, but I think this is a bad example because the "facts" on the ground changed significantly in the time period.
I did not say this.
I'm illustrating the original poster's comment about these forecasts being guesses of likelihood.
Of course Nate Silver and co. did not have Comey reopening the case as a factor in their models; that is not an indictment of the model itself.
Yet I'm sure all of us knew folks who had opinions riding on the 85%+ forecasts, and then losing faith in the predictions as they wildly changed over the course of weeks.
As you say, "88% chance of winning" is not "expected to receive 88% of the vote".
The 538 model attempted to weigh the reliability (recency, reputation, magic pixie dust) of polling data and project a range of outcomes.
And even with a "perfect" model, it can take a while to absorb exogenous events like the Comey surprise.
The causes of 538's prediction error might be unknowable. Or, to be fair, if it was even an error! Would we expect probability to approach 100% in the moments before polling opens? Maybe in some fields, but 538 did not attempt this. IIRC they ended at ~70/30 Clinton. A single roll of a die (1d6) will frequently come up 1 or 2.
Why is that not an indictment of the model? Stuff happens in politics. Things change.
A month out you should ordinarily have much less certainty than a day before. But their predictions were the opposite, where certainty was falling. Sure, there can be reasons for that kind of inversion, but usually it's just arrogance and neglecting the long tail of black swans.
"FBI Director going rogue the week before the election" isn't something you could factor into a prediction because it just hadn't ever happened before. It'd be like trying to factor in "What if an asteroid hits Kansas the week before?"
It is funny seeing this here because it is a great example of how it is hard to fight misinformation.
What you said is technically correct but it is extremely misleading. There is no reason to use 538's projection a month out from the election when you could be using the one from the day of the election which had Clinton at 71%. You seem to have chosen the moment in which Clinton's odds were the highest to suggest the projection was wrong. Your comment is just as factual as if I said "538 was one of the few outlets that had Trump favored a few months before the election". That would also be technically true but it glosses over the fact that they only had Trump favored on a single day out of the several months they did projections.
Is this "misinformation" meant to smear 538? Is this just run-of-the-mill bias? Is this an honest mistake? It this specific date chosen intentionally and your motive is just being misunderstood? There is no way for a third party to know the definitive answer to these questions, but if I was 538 I would certainly feel a little attacked by your comment and might jump to calling it misinformation.
That projection was made scant weeks out from the election, as well. It's not irrelevant (Oct. median was 85%), and calling my providing a link misinformation is pretty bizarre.
I suspect this is not the first time you've felt obliged to stick up for 538 but you're purely wielding a strawman in this case. I've expressed no judgement.
Anyway, we're talking about the general populace's sentiments around the predictions. Why would we possibly talk about the predictions made the day of the election – those numbers had done no work in shaping that sentiment.
No, because that 88% was basically a prediction of a prediction because as other people pointed out that occurred before news that changed the makeup of the race. You can't blame them for not knowing the news ahead of time.
It would be like if I predicted the Rams win the Superbowl this weekend, then we find out on Saturday that 10 players will miss the game due to Covid. I might then revise my prediction to the Bengals winning. If the Rams win wouldn't you say my prediction was wrong because of my final prediction? My initial prediction might have been right but that was made with less information and I revised that prediction once I got more information.
Similarly it doesn't make sense to criticize 538 for being less accurate with their early projections when they had less information. As they got more information their predictions became more accurate. It should be obvious that they weren't changing their model in a vacuum to push the odds towards Trump. More information was coming out that improved Trump's odds and the model reflected that.
And to be clear I didn't call your comment misinformation. I used it as an example of why it is hard to categorize misinformation. Some might view your comment as misinformation and some might not. The only value judgement I made was that it is "extremely misleading" and I stand by the categorization regardless of the motive behind your comment.
It must be a good feeling, then, that I have not criticized them.
> to be clear I didn't call your comment misinformation
Earlier:
> Is this "misinformation" meant to smear 538?
You were trying to correct someone who was defending the accuracy of the general industry predictions. If you were not directly criticizing 538, the criticism was certainly implied.
>> Is this "misinformation" meant to smear 538?
Are you familiar with the concept of scare quotes? I specifically used quotes there to indicate that I was not directly calling your comment misinformation but was instead using that term with some detachment.
And the way statistics work, a 90% forecast is truly a 90% forecast - they weren't wrong with this. It's just people think 99% chance of winning basically means "they won". But that's not how it works. So the idea that these numbers are misinformation is incorrect, it's that media is using a metric that the average person has trouble comprehending.
Isn’t that a clear case of disinformation?
Something like this only rises to the level of disinformation if the media (or whoever) deliberately presents an accurate piece of data in a way that it knows will not be understood.
If metrics that average people don't understand was disinformation than 90% of my job would be disseminating disinformation. It's not. Instead, a large part of my job is explaining the metrics.
It is probably impossible to have the complex dialogue sufficient to inform people both intelligent and willing to put in the work in a way that is not apt to either be misunderstood accidentally or more frequently on purpose.