DaleSpam said:
No. It was an oversight.
DaleSpam said:
If the model depends on knowledge and the result of the model is a probability then how can you claim that probability does not depend on knowledge? And I agree that it is not peculiar to probability.
Because this sort of dependence of knowledge is universal to every discussion, hence adds no information to the discussion. It is like emphasizing in a discussion of a computer program ''programs depend on knowledge'' - true but not relevant for the substance of what a computer program is.
Knowledge needs no mention in discussing deterministic models, so it creates an undue and misleading emphasis if mentioned for probabilities. The usual usage there suggests that the dependence of probability on knowledge somehow explains its peculiar nature, while in fact it acts as a smoke screen hiding the real issues.
DaleSpam said:
I think you are confusing your concept of "subjective" with knowledge. With a specified family of priors and an algorithm for determining the hyper parameters from the available knowledge then the probability depends on the knowledge objectively. I believe that you are really just saying that scientists shouldn't just use subjective "gut feeling" priors.
I am saying more:
With a specified family of priors and an algorithm for determining the hyper parameters from a set of data then the probability depends on the data objectively. Independently of whether the data arise from knowledge, simulation from a hypothetical source, prejudice, fraud, divination, or anything else.
That it depends on knowledge if the data depend on knowledge is true but irrelevant.
The model is only as good as the data, that's the only relevant point here.
DaleSpam said:
This whole debate is purely semantic.
Of course. It is a matter of precise usage of the concepts. Semantics is important in interpretation issues.
DaleSpam said:
If you require probabilities to be defined only over an ensemble then the probabilities do not depend on knowledge (for Bayesians the posterior is not a function of the prior given an infinite amount of data).
But one is never given that much data.
DaleSpam said:
If you allow probabilities to be defined over individual trials or small samples then the posterior is a function of the prior so the probabilities do depend on knowledge.
No. it depends on the sample, which could come from a computer simulation rather than from real data. It depends on knowledge only if the sample represents the knowledge someone has about the intended application; so mentioning knowledge is less accurate and makes more unspoken assumptions.
What if nobody has ever seen the data but the computer program processing it? Does the program then know? Or does the human who started the program know? Knowledge is a philosophically difficult concept prone to misunderstanding.
DaleSpam said:
That dependence on knowledge may be objective if you have a well-defined rule for generating a prior based on the knowledge, or it may be subjective if you have a "gut feeling" prior.
If you substitute ''knowledge'' by ''data'' I'd agree. The latter is a much more descriptive word.
Why substitute it with an unspecific word that assumes that there is someone having the knowledge and invites associations with states of the mind of experimenters?