I answered a different question than what this sits below, but I think that the answer is still both. B is probably the one that fits in the formulas, but you should also remember that the cases where B/=F are the cases where such formulas are least likely to serve you well.
Yep. To expand: correctly used, they should not contradict each other. If they give different answers, then at least one of them is being used in a way in which it is not applicable.
You’re right, so far as it goes, but I don’t think it gets you very far. My point is that this dodges what the debate is about. Proponents of F say that it should be used for doing inductive inference while proponents of B say they’re wrong, B is what should be used. If you’re not answering that question, you’re not settling the debate.
Now if you’re not trying to settle the debate, then we have no argument.
Well, the only debates I’m claiming to definitively settle are the philosophical ones about “what does probability really mean?”, “are 0 and 1 really probabilities?” and suchlike, over which I’ve seen enough electrons spilled that I considered it well worth trying to put them to rest.
But in a typical inductive scenario, it seems to me that since we can’t work directly with F, whereas we can work directly with B, Bayesian reasoning is the appropriate tool to use. Do you have any counterexamples in mind where the two approaches give different answers and the difference can’t be resolved by noting that they aren’t answering the same question?
Do you have any counterexamples in mind where the two approaches give different answers and the difference can’t be resolved by noting that they aren’t answering the same question?
Sure, B and F don’t directly contradict each other, but which one should we use when reasoning under uncertainty?
edit: better statement of what I was getting at
I answered a different question than what this sits below, but I think that the answer is still both. B is probably the one that fits in the formulas, but you should also remember that the cases where B/=F are the cases where such formulas are least likely to serve you well.
Yep. To expand: correctly used, they should not contradict each other. If they give different answers, then at least one of them is being used in a way in which it is not applicable.
You’re right, so far as it goes, but I don’t think it gets you very far. My point is that this dodges what the debate is about. Proponents of F say that it should be used for doing inductive inference while proponents of B say they’re wrong, B is what should be used. If you’re not answering that question, you’re not settling the debate.
Now if you’re not trying to settle the debate, then we have no argument.
Well, the only debates I’m claiming to definitively settle are the philosophical ones about “what does probability really mean?”, “are 0 and 1 really probabilities?” and suchlike, over which I’ve seen enough electrons spilled that I considered it well worth trying to put them to rest.
But in a typical inductive scenario, it seems to me that since we can’t work directly with F, whereas we can work directly with B, Bayesian reasoning is the appropriate tool to use. Do you have any counterexamples in mind where the two approaches give different answers and the difference can’t be resolved by noting that they aren’t answering the same question?
Well, no, but but proponents of F may disagree.