Nate Silver

@NateSilver538 ↗

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Last Checked Nov. 11, 2020

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Wed May 20 14:39:10 +0000 2020

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Nate Silver @NateSilver538

Yeah for sure. And trying to manually remove "bad" data points without taking the time to develop a systematic process/philosophy for doing so (i.e. building an algorithm) introduces an awful lot of subjectivity. — PolitiTweet.org

@NateSilver538 I think a good general principle is to almost never throw out data when trying to forecast or make a… https://t.co/vIYuXX2ehl

Posted May 20, 2020 Hibernated

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Nate Silver @NateSilver538

@mattyglesias There can also be the issue of overkill, e.g. pollsters introduce 3 or 4 changes to try to combat D bias. It turns out only one of those changes (e.g. education weighting) is correct. The other ones introduce an R bias. That's basically what happened in the UK in 2017. — PolitiTweet.org

Posted May 20, 2020 Hibernated

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Nate Silver @NateSilver538

Subjectivity (which you want to avoid) vs. judgment (which all models require) is admittedly a fine line. But generally speaking, you should strongly prefer finding systematic rather than ad-hoc methods for handling "problematic" cases. — PolitiTweet.org

Posted May 20, 2020 Hibernated