This statement avoids every point that I made. That's apparently your strategy. You pick and choose what to respond to so as to make yourself look as good as possible.
I'm not a self-anointed (or even self-appointed) expert
on Bayesian statistics. In fact, I
reject Bayesian epistemology. I am on this site looking for someone who supports it so that I can have an interesting discussion. Bayesian epistemology is supposed to overcome all the logical fallacies of the scientific method. I am skeptical that such a thing is possible.
Modus ponens is not a subject for Bayesian statistics. Bayesian statistics exists so that one can consistently and mathematically update one's subjective degree of belief in something. Modus ponens is out of scope.
No. The probability of Bob ordering fish is an unknown variable. Regardless whether you assume that he likes or doesn't like fish, his probability of ordering fish will remain unchanged. What will change is
your subjective degree of belief.
This is a bad example because what you did has nothing to do with the logical consequences of whether Bob will order fish. A far better comparison would be to say, "If I assume that Bob orders fish, then it will become 100% probable that Bob will order fish." It's still a wrong statement, but it's far closer to what you said initially.
No, you're the confused one. Even if you assume that Bob orders only fish, the probability of him ordering fish does not go to 1. Your subjective degree of belief may be higher (certainly not 1, assuming that you are rational). However, Bob's actual probability of ordering fish does not change. It remains unknown.
My Christians? I don't have any Christians. Slavery is not legal where I live. Why would my hypothetical Christians and you use circular reasoning? Don't you know that this is a formal logical fallacy?
Again, you're completely misusing the formula. There's no probability that God exists. God is not something that exists 60 percent of the time (to make up a number) whereas Bob may order fish 60 percent of the time that he's at that restaurant. Such an occurrence could be open to a frequentist description of Bob's habits. If Bob orders fish 60 percent of the time, then his statistical likelihood of ordering fish is 0.6. Bayesian statistics exist to allow for the measurement of a
subjective degree of belief in something that occurs only once. One cannot, for example, put Jesus in Jerusalem 100 times and see how many times out of 100 he gets crucified for proclaiming himself. It is something that either
happened or
did not happen. It's not for us to measure the probability that Jesus gets crucified. It's for us to determine whether we believe that this actually happened based on the evidence that can be collected. Of course, some people may assign ridiculously high or low
a priori probabilities of the same based on alogical arguments, such as "My mommy said the Bible is 100% true so, let's start with 0.999999 as an initial probability." That's why Bayesian epistemology is basically worthless without principles that mandate a certain starting probability. It doesn't matter whether you call the tool
the principle of indifference,
the principle of insufficient reason,
the principle of maximum ignorance, or
the principle of maximum entropy.
I was wondering the same thing!
Set theory is a tool, and yes I'm familiar with it. Of course, I'm also familiar with
Russell's Paradox, which shows that set theory is irreparably flawed. If you find it useful, then good for you. However, don't think that an appeal to set theory is going to save you.
A predicate is the part of a sentence that is not the subject.
Are you criticizing or are you combating Boggarts?
First of al, I have no idea why you are so enamored of this formula. I can only assume that you did some Googling and came up with it, and you're trying to beat me over the head with it. However, if you look back at
, you will see that the formula I included was:
and this is
NOT THE FORMULA YOU ARE USING. So again, I am firmly convinced that your formula and examples are all about you trying (and failing) to prove yourself smarter than others rather than actually addressing the issue at hand.
As you can see, the graphic I posted clearly shows the
probability of the hypothesis given the evidence. It's not the probability of the hypothesis
given the hypothesis. So you can clamp your hands over your ears, and yell "nya, nya, nya, I can't hear you" all you want, but you'll never convince me that (mis-)using another formula is going to refute the proper use of the one I used.[/URL]