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“Statistics: Learning from stories” (my talk in Zurich on Tues 28 Aug)

Statistics: Learning from stories

Andrew Gelman, Department of Statistics and Department of Political Science, Columbia University, New York

Here is a paradox: In statistics we aim for representative samples and balanced comparisons, but stories are interesting to the extent that they are surprising and atypical. The resolution of the paradox is that stories can be seen as a form of model checking: we learn from a good story when it refutes some idea we have about the world. We demonstrate with several examples of successes and failures of applied statistics.

Information on the conference is here.


  1. Are they recording the talk and putting it online? I’d love to see it.

    (An aside: I presented at the Swiss Stats meeting years ago. It’s a fun conference!)

  2. Thanatos Savehn says:

    The Law and Statistics merge. This idea that the job of jurors is to assess each proffered model, and thereafter declare which one best fits the stories being told by the competing sides, is where I live.

    • Keith O'Rourke says:

      > assessing each proffered model, and thereafter declaring (accepting) which one(s) best fit the stories (possible realities one is facing)

      I believe that starts in early childhood for most humans and perhaps in some animals – why does it become so strange in Law and Statistics?

      Definitely more deliberate assessment (and checking) but in essence just the same underlying processes on _steroids_?

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