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I'm turned off by the invocation of quantum mechanics here. Most applications of Bayesian statistics have nothing to do with QM, so "it's not compatible with QM
by blt 7y ago
I'm turned off by the invocation of quantum mechanics here. Most applications of Bayesian statistics have nothing to do with QM, so "it's not compatible with QM" doesn't seem like a strong argument.
QM is the number-one favorite topic of crank scientists and pseudoscience. When using it in the discussion of a seemingly-unrelated topic, authors should take extra care to motivate why QM is relevant.
(Of course probability theory and QM are not unrelated topics, but probability exists independently of QM.)
- pc2g4d 7y agoI think they're assessing how universally applicable Bayesian reasoning is, and think they're seeing a limit in the quantum realm.
- syntonym2 7y agoWhile reading the blog post/abstract I had the same thought, but the full paper makes it clear that the author intends something different: > The second challenge that the uncertainty principle poses for Bayesian statistics is that [...] we routinely treat the act of measurement as a direct application of conditional probability. Furthermore it states that this problem might also arise for other applications of Bayesian statistics: > If classical probability theory needs to be generalizedto apply to quantum mechanics, then it makes us wonder if it should be generalized for applicationsin political science, economics, psychometrics, astronomy, and so forth. It’s not clear if there are any practical uses to this idea in statistics, outside of quantum physics. For example, would it make sense to use “two-slit-type” models in psychometrics, to capture the idea that asking one question affects the response to others?