Is pluralism the correct philosophical interpretation of probability?
I saw this really interesting question on stackexchange:
https://philosophy.stackexchange.com/questions/115010/is-pluralism-the-correct-philosophical-interpretation-of-probability
I don't know if I've seen a conversation like this here before, maybe there's more interesting things to say about it than what was said so far on stackexchange.
It seems to me like frequentism is kinda a default almost, and it intuitively makes sense in some scenarios but not all scenarios, and so we need a more analytical intepretation of probability to supplement and work with frequentism to make probabilities make sense all the time. What do you think?
https://philosophy.stackexchange.com/questions/115010/is-pluralism-the-correct-philosophical-interpretation-of-probability
I don't know if I've seen a conversation like this here before, maybe there's more interesting things to say about it than what was said so far on stackexchange.
It seems to me like frequentism is kinda a default almost, and it intuitively makes sense in some scenarios but not all scenarios, and so we need a more analytical intepretation of probability to supplement and work with frequentism to make probabilities make sense all the time. What do you think?
Comments (8)
What scenarios doesn't frequentism work for? I had a quick skim through the Stanford entry and believe it said something to the effect that frequentism is a subset of Bayesianism. This seemed odd to me as aren't all probability methods subject to Bayesianism?
Seems like frequentism is a bad fit for "What's the probability that Donald Trump wins the election?" for example.
It's not like there's a like-for-like set of comparable situations you can compare this future event to, like you would with coin flips for example - this next election will happen once and will be unique from all elections before and after it.
by Aubrey Clayton that points out some of the major flaws in frequentism as it is commonly put forth.
I think it's very accessible as far as math books go, and does a very good job explaining the history, even if it does sometimes seem to lurch close ad hominems in pointing out how many advocated of frequentism were social scientists trying to use statistics to advocate for eugenics.
However, I am not convinced, as Clayton seems to be, that Bayesian methods resolve the problem.
I actually think that the widespread use of information theory in the sciences (particularly physics) and as a tool to unify the sciences will make this question among the very most important questions in metaphysics in the future. If you're defining physical reality in terms of information, and defining causation in terms of computation and information transfer, then "what is information," becomes an essential question. But information is itself generally defined in terms of probability.
There is an argument that information doesn't "really" exist because in reality there is no "probability." For any system the measurements/interactions that can occur are just the measurements that do actually occur. Information is thus inherently "subjective." But since the concept is so foundational it seems that the consensus tends towards "well so much the worse for (that sort of) objectivity," and you even see arguments for information being more ontologically basic than matter or energy, the latter emerging from the former. Obviously, the merits of such positions, or even what they are saying, will depend on one's understanding of probability in the first place.
Quoting flannel jesus
I think we predict such probabilities almost exclusively from national and constituency polling, and projections based upon said national and constituency polling. At least here in the UK.
In any event, we judge probabilities based upon patterns of behaviour?
Maybe not, maybe it's just all obviously fitting into a frequentist paradigm and I'm a silly boy.
Quoting flannel jesus
I can only think of patterns of behaviour being a basis for judging probability. Which I think the definition of frequentism fits.