What has it come to, this sensible life?
On Apr 16, 2012, at 3:58 PM, Mitchell Tsai <tsai@cs.ucla.edu> wrote:
> Frank,
>
> This is where Bayesian theory (and more accurate "a priori" beliefs)
> allow more accurate probability calculations.
>
> If you use past data, and assume P(all events) = equal, then you often
> run into pre-selection bias; e.g. I picked a weird set of data.
> So Bayesian analysis will use P(my data set is unusual) = whatever you
> set.
>
> Another example, say I'm considering video poker games in Las Vegas at
> 1) major casino in Las Vegas - P(prior belief in gaffed machine) < 0.01
> 2) non-name casino at Indian reservation where other people are
> reporting suspicious result - P(prior belief in gaffed machines) = 0.25
>
> Then P(belief machine is gaffed after test | prior belief) = function
> of test result and P(prior belief in gaffed machines).
>
> If you use a non-random set of data (e.g. data you have gathered
> before), then
> P(belief machine is gaffed) = function of test result and P(prior
> belief in gaffed machines) and selection-bias-in-original test)
>
> Mitchell
>
> A similar example of selection-bias is one about weather.
> My friend tells me that last week it rained 6 out of 7 days, and they
> ask how unusual that is...
>
> Most people will just calculate how unlikely it is to have rain 6 of 7
> days.
> A better calculation will take into account that my friend is only
> telling me this because it is "somehow weird" (e.g. no royals in
> 120,000 hands)
> and factor in the "selection-bias".
>
I have no idea what you just said.
TC___
[Non-text portions of this message have been removed]
