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Why do they get praise for their 2012 predictions but get a pass for their 2016 mispredictions? If they gave Trump a 30% chance to win and, as you say, it is pe

by typon 8y ago

Why do they get praise for their 2012 predictions but get a pass for their 2016 mispredictions? If they gave Trump a 30% chance to win and, as you say, it is perfectly ordinary for a 30% chance event to happen, then what is the point of their prediction? What is the point of listening to someone who can never be wrong?

gault8121 8y ago
Yes, the projections are essentially useless. Nassim Taleb does a great job of laying this out - basically, the projections create a false sense of certainty onto a highly uncertain set of events. https://towardsdatascience.com/why-you-should-care-about-the-nate-silver-vs-nassim-taleb-twitter-war-a581dce1f5fc https://towardsdatascience.com/why-you-should-care-about-the... https://math.stackexchange.com/questions/1911110/what-is-nassim-talebs-criticism-of-538s-election-model https://math.stackexchange.com/questions/1911110/what-is-nas...
lazzlazzlazz 8y ago
If I have the ability to predict coin tosses correct 55% of the time, that would be incredible - an almost unreal talent. And I'd be wrong 45% of the time. For any one prediction, it's hard to say that a probability distribution is "wrong", but across many predictions, we can definitely evaluate the accuracy of a predictor and quantify whether they're useful or not. 538 has an excellent track record.
- idDriven 8y ago
  I know Mythbusters isn't the most scientific, but when they tested this, although with a small sample size so it could be off, if you choose Tails every time you should hit well over 55% based on the weight distribution of the coin.
thousandautumns 8y ago
They can be wrong. The problem is that you are looking at a single data point. Judging their performance requires viewing all of their predictions, across all elections, and seeing how often their predicted probabilities match up with outcomes. Do the people they give a 30% chance of winning win 30% of those races? Do the people they give a 60% chance of winning win 60% of those races? That is how you judge their performance, and from that lens they do quite well.

by typon 8y ago

gault8121 8y ago

Yes, the projections are essentially useless. Nassim Taleb does a great job of laying this out - basically, the projections create a false sense of certainty onto a highly uncertain set of events. https://towardsdatascience.com/why-you-should-care-about-the-nate-silver-vs-nassim-taleb-twitter-war-a581dce1f5fc https://towardsdatascience.com/why-you-should-care-about-the... https://math.stackexchange.com/questions/1911110/what-is-nassim-talebs-criticism-of-538s-election-model https://math.stackexchange.com/questions/1911110/what-is-nas...

lazzlazzlazz 8y ago

If I have the ability to predict coin tosses correct 55% of the time, that would be incredible - an almost unreal talent. And I'd be wrong 45% of the time. For any one prediction, it's hard to say that a probability distribution is "wrong", but across many predictions, we can definitely evaluate the accuracy of a predictor and quantify whether they're useful or not. 538 has an excellent track record.

idDriven 8y ago
I know Mythbusters isn't the most scientific, but when they tested this, although with a small sample size so it could be off, if you choose Tails every time you should hit well over 55% based on the weight distribution of the coin.

thousandautumns 8y ago

They can be wrong. The problem is that you are looking at a single data point. Judging their performance requires viewing all of their predictions, across all elections, and seeing how often their predicted probabilities match up with outcomes. Do the people they give a 30% chance of winning win 30% of those races? Do the people they give a 60% chance of winning win 60% of those races? That is how you judge their performance, and from that lens they do quite well.