[FRIAM] Learning about Bayesian Statistics
Barry MacKichan
barry.mackichan at mackichan.com
Tue Feb 5 16:20:31 EST 2019
Isn’t that what Friday mornings are about?
--Barry (Bonzo)
On 4 Feb 2019, at 15:48, Nick Thompson wrote:
> Thanks, everybody, for these suggestions.
>
>
>
> I should be able to manage extracting data from primates, since that
> is what my phd was in.
>
>
>
> N
>
>
>
> Nicholas S. Thompson
>
> Emeritus Professor of Psychology and Biology
>
> Clark University
>
> <http://home.earthlink.net/~nickthompson/naturaldesigns/>
> http://home.earthlink.net/~nickthompson/naturaldesigns/
>
>
>
> From: Friam [mailto:friam-bounces at redfish.com] On Behalf Of Roger
> Critchlow
> Sent: Monday, February 04, 2019 8:24 AM
> To: The Friday Morning Applied Complexity Coffee Group
> <friam at redfish.com>
> Subject: Re: [FRIAM] Learning about Bayesian Statistics
>
>
>
> You could also look at Richard McElreath's Statistical Rethinking: A
> Bayesian Course with Examples in R and Stan, a book, software package,
> and youtube lectures. McElreath is an anthropologist who studies the
> development of social learning in primates, so naturally he teaches a
> statistics course for natural and social scientists focused on getting
> data to answer scientific questions. The first two lectures explain
> why Bayes and why an anthropologist is teaching statistics.
>
>
>
> https://www.youtube.com/watch?v=4WVelCswXo4
> <https://www.youtube.com/watch?v=4WVelCswXo4&list=PLDcUM9US4XdNM4Edgs7weiyIguLSToZRI>
> &list=PLDcUM9US4XdNM4Edgs7weiyIguLSToZRI
>
>
>
> -- rec --
>
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>
>
> On Mon, Feb 4, 2019 at 8:28 AM Edward Angel <angel at cs.unm.edu
> <mailto:angel at cs.unm.edu> > wrote:
>
> You might also like Nate Silver’s book “The Signal and the
> Noise”. It’s almost non technical and has interesting examples of
> the use and non use of Bayesian reasoning from the house market
> collapse to evaluating baseball players.
>
>
>
> Ed
>
> ____________
>
>
>
> Ed Angel
>
> Founding Director, Art, Research, Technology and Science Laboratory
> (ARTS Lab)
> Professor Emeritus of Computer Science, University of New Mexico
>
> 1017 Sierra Pinon
>
> Santa Fe, NM 87501
> 505-984-0136 (home) angel at cs.unm.edu <mailto:angel at cs.unm.edu>
>
> 505-453-4944 (cell) http://www.cs.unm.edu/~angel
>
>
>
>
>
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>
>
> On Feb 3, 2019, at 12:03 AM, George Duncan <gtduncan at gmail.com
> <mailto:gtduncan at gmail.com> > wrote:
>
>
>
> At Friday's church service Nick asked about how one might learn the
> basics of Bayesian statistics. I said I would think about it, and so
> here are my conclusions.
>
>
>
> For historical and philosophical background: Read The Emergence of
> Probability by Ian Hacking
>
>
>
> For a systematic course: Take Coursera, Bayesian Statistics, a course
> from Duke University with a 7-day free trial.
>
>
>
> Also of course there are several reasonable texts on Bayesian
> Statistics.
>
>
>
> George Duncan
>
> Emeritus Professor of Statistics, Carnegie Mellon University
> georgeduncanart.com <http://georgeduncanart.com/>
>
> See posts on Facebook, Twitter, and Instagram
>
> Land: (505) 983-6895
>
> Mobile: (505) 469-4671
>
>
> My art theme: Dynamic exposition of the tension between matrix order
> and luminous chaos.
>
>
>
>
> "Attempt what is not certain. Certainty may or may not come later. It
> may then be a valuable delusion."
>
>
> From "Notes to myself on beginning a painting" by Richard Diebenkorn.
>
>
> "It's that knife-edge of uncertainty where we come alive to our truest
> power." Joanna Macy.
>
>
>
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> ============================================================
> FRIAM Applied Complexity Group listserv
> Meets Fridays 9a-11:30 at cafe at St. John's College
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> ============================================================
> FRIAM Applied Complexity Group listserv
> Meets Fridays 9a-11:30 at cafe at St. John's College
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