Nate Silver

@NateSilver538 ↗

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Last Checked March 15, 2021

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Tue Sep 01 16:00:28 +0000 2020

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Nate Silver @NateSilver538

We spend a lot of time setting up these mechanics. It's a hard problem. It's tricky because it's hard to distinguish say a 1-in-1,000 chance from a 1-in-100,000 chance given the paucity of data in presidential elections. — PolitiTweet.org

Posted Sept. 1, 2020 Hibernated

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Nate Silver @NateSilver538

In one sim, for example, the model might randomly draw a map where Biden underperforms its projections with college-educated voters but over-performs with Hispanics. In that case, might win AZ but not VA. Or, if Biden happens to win MO in one simulation, he'll often win KS too. — PolitiTweet.org

Posted Sept. 1, 2020 Hibernated

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Nate Silver @NateSilver538

But we want our projections to reflect real-world uncertainties as much as possible, including model specification error. There are many gray areas here, and there are certain contingencies we don't account for (e.g. widespread election tampering) but that is the general idea. — PolitiTweet.org

Posted Sept. 1, 2020 Hibernated