Basically frequentism says there is some preexisting distribution of probabilities, a sample space, that once understood can predict all probabilities. This is an "objectivist" perspective. Bayesian statistics says for practical work this does not exist, we must use what limited knowledge we have to make an estimate, a Bayesian prior, and then compute a probability outcome. This can be repeated in a regression. In the end for N --> infinity frequentism and Bayesianism effectively converge to the same result.
LC On Sunday, December 4, 2022 at 10:24:57 PM UTC-6 agrays...@gmail.com wrote: > How can the frequentist theory of probability be applied to a system, such > as the H atom, which has an infinite set of possible outcomes for all > energy level transitions? AG > -- 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 everything-list+unsubscr...@googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/everything-list/05e66ec5-5d77-4078-9aa0-b178d897ffccn%40googlegroups.com.
