From: Lee Corbin (lcorbin@tsoft.com)
Date: Mon Jul 07 2003 - 20:41:10 MDT
Mitchell writes
> But what I still don't get is what's wrong with
> 'orthodox statistics'. I obtained my p1/(p1+p2)
> through frequentist thinking, which is supposed to
> be anathema to Bayesians. On the SL4 list, Ben
> Goertzel implies that "non-Bayesian probabilists"
> are restricted in their choice of priors:
> http://sl4.org/archive/0305/6820.html
>
> ... but even if what he says is true, I don't
> see it reflecting on the subjectivist-vs-frequentist
> debate. Both sides need priors to get anywhere,
> and there's nothing in frequentism to *compel* the
> use of Gaussian priors. So, I still don't get the
> philosophical lesson.
I can't answer your question, but did you check out problem
number three on my list? Apparently Bayesian statisticians
can solve it whereas those like me trained in classical
mathematics, do not have enough information. I'm still in
shock that not in all instances does P(A & B) = P(A|B)*P(B)
according to the Bayesians.
Anyway, problem number three is hopefully my long sought
Rosetta Stone that does not require talking of distributions
to see Bayesianism rear its head. (I do have one smaller
and much easier problem that lies bare the differences, but
this here might be much hotter stuff.)
> 3. The probability that a newborn will have deformities
> traceable to a sickness of its mother during pregnancy is 1%.
> If a child is born healthy and normal, the probability that
> the mother had rubella during her pregnancy is 10%. If a
> child is born with deformities that can be traced to a
> sickness of the mother, the probability that the mother had
> rubella during her pregnancy is 50%. What is the probability
> that a child will be born with deformities if its mother had
> rubella during her pregnancy?
Lee
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