What did Nate Silver just say? Blogging the JSM 2013

imagesMemory Lane: August 6, 2013. My initial post on JSM13 (8/5/13) was here.

Nate Silver gave his ASA Presidential talk to a packed audience (with questions tweeted[i]). Here are some quick thoughts—based on scribbled notes (from last night). Silver gave a list of 10 points that went something like this (turns out there were 11):

1. statistics are not just numbers

2. context is needed to interpret data

3. correlation is not causation

4. averages are the most useful tool

5. human intuitions about numbers tend to be flawed and biased

6. people misunderstand probability

7. we should be explicit about our biases and (in this sense) should be Bayesian?

8. complexity is not the same as not understanding

9. being in the in crowd gets in the way of objectivity

10. making predictions improves accountability

Just to comment on #7, I don’t know if this is a brand new philosophy of Bayesianism, but his position went like this: Journalists and others are incredibly biased, they view data through their prior conceptions, wishes, goals, and interests, and you cannot expect them to be self-critical enough to be aware of, let alone be willing to expose, their propensity toward spin, prejudice, etc. Silver said the reason he favors the Bayesian philosophy (yes he used the words “philosophy” and “epistemology”) is that people should be explicit about disclosing their biases. I have three queries: (1) If we concur that people are so inclined to see the world through their tunnel vision, what evidence is there that they are able/willing to be explicit about their biases? (2) If priors are to be understood as the way to be explicit about one’s biases, shouldn’t they be kept separate from the data rather than combined with them? (3) I don’t think this is how Bayesians view Bayesianism or priors—is it? Subjective Bayesians, I thought, view priors as representing prior or background information about the statistical question of interest; but Silver sees them as admissions of prejudice, bias or what have you. As a confession of bias, I’d be all for it—though I think people may be better at exposing other’s biases than their own. Only thing: I’d need an entirely distinct account of warranted inference from data.

This does possibly explain some inexplicable remarks in Silver’s book to the effect that R.A. Fisher denied, excluded, or overlooked human biases since he disapproved of adding subjective prior beliefs to data in scientific contexts. Is Silver just about to recognize/appreciate the genius of Fisher (and others) in developing techniques consciously designed to find things out despite knowledge gaps, variability, and human biases? Or not?

Share your comments and/or links to other blogs discussing his talk (which will surely be posted if it isn’t already). Fill in gaps if you were there—I was far away… (See also my previous post blogging the JSM).

For a follow-up post including an 11th bullet that I’d missed, see here.Photo on 8-4-13 at 3.40 PM

[i] What was the point of this, aside from permitting questions to be cherry picked? (It would have been fun to see ALL the queries tweeted.) The ones I heard were limited to: how can we make statistics more attractive, who is your favorite journalist, favorite baseball player, and so on. But I may have missed some, I left before the end.

Some reader comments on JSM 14 are here. Feel free to add comments here or there on either JSM.


Categories: Statistics, StatSci meets PhilSci

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3 thoughts on “What did Nate Silver just say? Blogging the JSM 2013

  1. I attended this year’s JSM. (Typing this in Boston, leaving tomorrow.)

    I was pleasantly surprised to hear several speakers in various sessions make statements like “If you are a Bayesian–which I am not–you might view it this way. Very polite, which is great, but I was glad that some people chose to express their status as a frequentist in public. 🙂 One speaker even said, “If you are willing to do a Bayesian analysis, you might try this method,” recognizing the fact that many are NOT willing.

    There were some worthwhile technical sessions, but to me the best by far a late-added on titled “Recent Concerns About Reproducibility and Replicability: The Statistical Aspects.” Lots of interesting (what I regard as) philosophy questions discussed there, as well as discussion of the disincentives against addressing them. 😦

    • Norm: Good to hear from you; it reminds me that we had some discussion on this last year. I hope readers check comments from the original post. I should note, also, that Christian Hennig wrote some remarks on JSM 14

      and readers can share any JSM14 reflections on either place.

      To get to Norm’s comment, I got the sense that this year might be a bit different, but on only the barest of evidence. It’s really great to hear “that some people chose to express their status as a frequentist in public”. It sounds quite funny to say this regarding an international statistics meeting, but I know just what you mean (Frequentist is not an “F” word!)

      [I wonder if it was possible this year to submit an abstract on “methodology” rather than only “Bayesian methodology” like last year.]

  2. Christian Hennig

    I posted something on Wednesday and Thusday in the other thread.

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