Wait, IlyaShipitser—I think you overestimate my knowledge of the field of statistics. From what it sounds like, there’s an actual, quantitative difference between Bayesian and Frequentist methods. That is, in a given situation, the two will come to totally different results. Is this true?
I should have made it more clear that I don’t care about some abstract philosophical difference if said difference doesn’t mean there are different results (because those differences usually come down to a nonsensical distinction [à la free will]). I was under the impression that there is a claim that some interpretation of the philosophy will fruit different results—but I was missing it, because everything I’ve been introduced to seems to give the same answer.
Is it true that they’re different methods that actually give different answers?
I think it’s more that there are times when frequentists claim there isn’t an answer. It’s very common for statistical tests to talk about likelihood. The likelihood of a hypothesis given an experimental result is defined as the probability of the result given the hypothesis. If you want to know the probability of the hypothesis, you take the likelihood and multiply it by the prior probability. Frequentists deny that there always is a prior probability. As a result, they tend to just use the base rate as if it were a probability. Conflating the two is equivalent to the base rate fallacy.
Wait, IlyaShipitser—I think you overestimate my knowledge of the field of statistics. From what it sounds like, there’s an actual, quantitative difference between Bayesian and Frequentist methods. That is, in a given situation, the two will come to totally different results. Is this true?
I should have made it more clear that I don’t care about some abstract philosophical difference if said difference doesn’t mean there are different results (because those differences usually come down to a nonsensical distinction [à la free will]). I was under the impression that there is a claim that some interpretation of the philosophy will fruit different results—but I was missing it, because everything I’ve been introduced to seems to give the same answer.
Is it true that they’re different methods that actually give different answers?
I think it’s more that there are times when frequentists claim there isn’t an answer. It’s very common for statistical tests to talk about likelihood. The likelihood of a hypothesis given an experimental result is defined as the probability of the result given the hypothesis. If you want to know the probability of the hypothesis, you take the likelihood and multiply it by the prior probability. Frequentists deny that there always is a prior probability. As a result, they tend to just use the base rate as if it were a probability. Conflating the two is equivalent to the base rate fallacy.
EY believes so.