On Sat, Feb 22, 2020 at 6:00 AM 'Brent Meeker' via Everything List < [email protected]> wrote:
> On 2/21/2020 2:41 AM, Bruce Kellett wrote: > > You still don't get it, do you? The argument applies to all possible bit > strings of length N. You do not get that from coin tosses in a single > world. It is only when you claim that all possible results exist in > separate branching worlds that the problem arises. So it is a problem for > your WM-duplication, and for Everett. But not for single world theories. > Statistical inference is perfectly intact as it is used in this world. > > > In the limit N->oo almost all worlds will observe results arbitrarily > close to the expected value. > What expected value? I think that is where the communication problem arises -- you seem to think that there is some over-riding "expected value". Whereas I take the view that each binary sequence from N Bernoulli trials is the data set from which some value of the probability is inferred -- and that can be any value from the interval [0,1]. So why isn't that enough for statistical inference? One path thru the > binomial branches of the MW is just like one sequence of bernoulli trials > in a single world in terms of its statistics? > Exactly. Or are you considering cases where p>0.5, so that simple one branch per > result doesn't work? > As I said, p can take on any value in the range [0,1]. I don't understand why you think that one branch per result doesn't work statistically. One branch per result does not agree with experience, but that is a different matter. Bruce -- You received this message because you are subscribed to the Google Groups "Everything List" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/everything-list/CAFxXSLSRzzNJxDAPcLNZaAqYPdMbwRnenuq4zoSxU_-pLGm8JA%40mail.gmail.com.
