Kishkumen wrote:OK, help me out here. The review I linked seems to me to say that Carrier actually blows his application of Baye's:Carrier correctly states that he is allowed to divide content between evidence and background knowledge any way he chooses, provided he is consistent. But then fails to do so throughout the book. For example on page 51 is an explanation of a ‘prior’ probability which explicitly includes the evidence in the prior, and therefore presumably in the background knowledge (emphasis original):
“the measure of how ‘typical’ our proposed explanations is a measure of how often that kind of evidence has that kind of explanation. Formally this is called the prior”
Going on to say (emphasis original):
"For example, if someone claims they were struck by lightning five times … the prior probabilty they are telling the truth is not the probability of being struck by lightning five times, but the probability that someone in general who claims such a thing would be telling the truth."
This is not wrong, per se, but highly bizarre. One can certainly bundle the claim and the event like that, but if you do so Bayes’s Theorem cannot be used to calculate the probability that the claim is true based on that evidence. The quote is valid, but highly misleading in a book which is seeking to examine the historicity of documentary claims.
If he blows it this badly, how can his methodology and results be sound?
Honestly, from the quote I'm not sure I understand Carrier's point was in this specific paragraph, nor do I understand exactly what the reviewer is taking issue with. A quote is "valid" and "not wrong, per se," yet is "highly misleading?" I can't comment on it more without reading the passage in context.
But isn't focusing on one error or bad example and then using it dismiss the work in its entirety the alleged go-to strategy of Classic Farms?
In any case, in the sciences that rely upon statistical inference, there have been debates going on for decades among members of the Bayesian Cult that think all statistical inference should be framed in Bayesian terms, and others that think Bayes' Theorem is but one specialized tool in a toolbox filled with many other things. 20 years ago I took an Econometrics course, and the teacher gave us a text that took the then-radical position that all Econometric inference should be done from a Bayesian framework. Now, there are probably over a dozen textbooks in print on Bayesian Econometrics.
Having lived through the Bayesian debate in that context and having been indoctrinated by the side that is now winning, I've become comfortable with the debate and confident in the Bayesian position. It's transparent to me that questions like "Did the historical Jesus exist" fit very neatly into the type of Bayesian inference that I believe is the best approach. I argued for that on the first page of this thread before I had even heard of Richard Carrier. In what I've read so far in On the Historicity of Jesus, Carrier is doing a decent job with the math.