Interesting Links for 3-10-2011

[andrewducker]

• This is how they gerrymander homeless children
  (tags: uk homeless housing politics)


• Why the world envies Mr Osborne
  (tags: GeorgeOsborne finance politics uk)


• Rick Perry's hunting ranch is called....Niggerhead.
  (tags: usa RickPerry racism politics)


• Homemade GPS Receiver
  (tags: GPS Electronics)


• Judge rules against Bayesian probability
  (tags: statistics law uk)


• Why This Year's Doctor Who Finale Was (Mostly) Better than Last Year's
  (tags:)


• The Pinboard people talk about the fallout from how badly Delicious fucked up.
  (tags: avos bookmarking fanfiction del.icio.us pinboard taxonomy)


• Cameron wants to scrap the Human Rights Act but Clegg won't let him
  (tags: libdem Conservatives politics rights uk)


• Historians Politely Remind Nation To Check What's Happened In Past Before Making Any Big Decisions
  (tags: TheOnion satire funny history)


• USA now assassinating its own citizens without due process
  (tags: usa law assassination murder)


• How cat videos get onto the internet
  (tags: cats videos youtube funny comic)

Comments

[purplecthulhu.livejournal.com]

Indeed, the prior is where I've had philosophical and technical issues with Bayesianism. But where there is good reason for a prior (a previous set of data for example), or where a variety of uniform priors don't affect the posterior, then I don't have a problem. They are in effect representing your ignorance of the system.

The prior, likelihood, posterior approach also explains why the same set of data can be taken as evidence for utterly different conclusions - eg. tea partyists and liberals. They're working from utterly different priors, which are there no matter what. Even if you're a frequentist.

[steer.livejournal.com]

is good reason for a prior (a previous set of data for example)

Where did that get its prior? :-)

here there is good reason for a prior (a previous set of data for example), or where a variety of uniform priors don't affect the posterior, then I don't have a problem

Absolutely -- in a symmetrical situation (the ball is under one of three cups) a uniform prior is perfect.

They're working from utterly different priors, which are there no matter what. Even if you're a frequentist.

Sure -- but having different outcomes from the same set of data (depending on prior) would not happen in frequentist analysis (and, a good Bayesian would say that the conclusions are not meaningful unless there was a reason to prefer one prior).

[purplecthulhu.livejournal.com]

You might be interested in this discussion on Prof Peter Coles' blog...

http://telescoper.wordpress.com/2011/10/06/bayes-in-the-dock/#entry

[steer.livejournal.com]

Interesting -- thanks for that.

My reading of the original redacted court document was that it was Bayesian statistics, not Bayes Theorem which the judge ruled against. The Guardian article muddies the water completely by using the two interchangably. The original court document is heavily redacted so it's unclear.

If the Prof you link to is right, it's a stupid ruling but I *think* he's working from the Guardian article not the court document. The rest of his column is interesting though.

[purplecthulhu.livejournal.com]

Do comment on Peter's blog if you wish - he likes to have new people visit!

[andrewducker]

Cheers, that was fascinating. And the conversation between you and Steer, likewise.