On Thu, Mar 5, 2020 at 1:34 PM 'Brent Meeker' via Everything List < [email protected]> wrote:
> On 3/4/2020 6:18 PM, Bruce Kellett wrote: > > > But one cannot just assume the Born rule in this case -- one has to use > the data to verify the probabilistic predictions. And the observers on the > majority of branches will get data that disconfirms the Born rule. (For any > value of the probability, the proportion of observers who get data > consistent with this value decreases as N becomes large.) > > > No, that's where I was disagreeing with you. If "consistent with" is > defined as being within some given fraction, the proportion increases as N > becomes large. If the probability of the an even is p and q=1-p then the > proportion of events in N trials within one std-deviation of p approaches > 1/e and N->oo and the width of the one std-deviation range goes down at > 1/sqrt(N). So the distribution of values over the ensemble of observers > becomes concentrated near the expected value, i.e. is consistent with that > value. > But what is the expected value? Does that not depend on the inferred probabilities? The probability p is not a given -- it can only be inferred from the observed data. And different observers will infer different values of p. Then certainly, each observer will think that the distribution of values over the 2^N observers will be concentrated near his inferred value of p. The trouble is that that this is true whatever value of p the observer infers -- i.e., for whatever branch of the ensemble he is on. 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/CAFxXSLREhH98Zg%2BsJCd-_tOp4vc%3DK0rStzvxnSdZPSgDqXqihw%40mail.gmail.com.
