Three questions for Nate Silver

1. “If people are so inclined to see the world through their tunnel vision, why suppose they are able/willing to be explicit about their biases?

2. “If priors are to represent biases, shouldn’t they be kept separate from the data rather than combined with them?

3. Lastly, putting aside questions 1 and 2 for the moment, doesn’t bias contaminate the Bayesian updating process altogether? For example, if I am biased in favor of X hypothesis being true, won’t my bias cause me to neglect or discount any evidence against my favored hypothesis?

Hat tip to Deborah Mayo, who posed questions #1 and #2 in her recent talk on science and statistics (check out slides 31-33 for a helpful summary of Professor Mayo’s take on the new “data journalism” generally). For our part, my wife and I posed question #3 in an email to Mr Silver long ago (December 2012) but have yet to receive a reply.

                So, what’s the cure for bias?

About F. E. Guerra-Pujol

When I’m not blogging, I am a business law professor at the University of Central Florida.
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2 Responses to Three questions for Nate Silver

  1. ryan44 says:

    I think that his point about biases was to acknowledge that they’re unavoidable. It’s impossible to make a scientific inquiry that is bias-free, so don’t pretend like you’re doing one.

    As a scientist, one of the things that people say that always sounds like nails on a chalkboard to my ears is that “we’re going to do an unbiased study”. There’s no such thing.

    Also, if you’re aware of the bias-variance tradeoff, you’d understand that “less biased” can translate into “more wrong” if you’re too far into the high variance side of the spectrum for the sake of unbiasedness.

    Priors are a separate issue, and in general prior != bias. Especially the way nate uses them since he defines a correct prior as one that is calibrated.

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