Could somebody point me in the direction of a good resource to learn the basics about Bayesian analysis, particularly as it may be applied to history? I'd like to be able to keep up here, mostly, and while I do know how to use Google , I figured I might need some help separating the wheat from the chaff.
Announcement
Collapse
Apologetics 301 Guidelines
If you think this is the area where you tell everyone you are sorry for eating their lunch out of the fridge, it probably isn't the place for you
This forum is open discussion between atheists and all theists to defend and debate their views on religion or nonreligion. Please respect that this is a Christianowned forum and refrain from gratuitous blasphemy. VERY wide leeway is given in range of expression and allowable behavior as compared to other areas of the forum, and moderation is not overly involved unless necessary. Please keep this in mind. Atheists who wish to interact with theists in a way that does not seek to undermine theistic faith may participate in the World Religions Department. Nondebate question and answers and mild and less confrontational discussions can take place in General Theistics.
Forum Rules: Here
This forum is open discussion between atheists and all theists to defend and debate their views on religion or nonreligion. Please respect that this is a Christianowned forum and refrain from gratuitous blasphemy. VERY wide leeway is given in range of expression and allowable behavior as compared to other areas of the forum, and moderation is not overly involved unless necessary. Please keep this in mind. Atheists who wish to interact with theists in a way that does not seek to undermine theistic faith may participate in the World Religions Department. Nondebate question and answers and mild and less confrontational discussions can take place in General Theistics.
Forum Rules: Here
See more
See less
Bayesian analysis for beginners
Collapse
X

Bayesian analysis for beginners
"I am not angered that the Moral Majority boys campaign against abortion. I am angry when the same men who say, "Save OUR children" bellow "Build more and bigger bombers." That's right! Blast the children in other nations into eternity, or limbless misery as they lay crippled from "OUR" bombers! This does not jell."  Leonard RavenhillTags: None

Originally posted by KingsGambit View PostCould somebody point me in the direction of a good resource to learn the basics about Bayesian analysis...as it may be applied to history?
2. Plug them into Bayes' formula
3. Voila, you get your desired final probability!

Originally posted by KingsGambit View PostCould somebody point me in the direction of a good resource to learn the basics about Bayesian analysis, particularly as it may be applied to history? I'd like to be able to keep up here, mostly, and while I do know how to use Google , I figured I might need some help separating the wheat from the chaff.
You can find a mathematical derivation of Bayes' theorem here: http://www.inf.ed.ac.uk/teaching/cou.../bayesCh7.pdf.
The Stanford Encyclopedia of Philosophy has a discussion of its relevance to epistemology: http://plato.stanford.edu/entries/ep...logybayesian/.
Some historical perspective on the theorem itself: http://lesswrong.com/lw/774/a_history_of_bayes_theorem/
Comment

Originally posted by Doug Shaver View PostSome would suggest that any input from me is chaff by definition. For what it's worth, though . . . .
You can find a mathematical derivation of Bayes' theorem here: http://www.inf.ed.ac.uk/teaching/cou.../bayesCh7.pdf.
The Stanford Encyclopedia of Philosophy has a discussion of its relevance to epistemology: http://plato.stanford.edu/entries/ep...logybayesian/.
Some historical perspective on the theorem itself: http://lesswrong.com/lw/774/a_history_of_bayes_theorem/"I am not angered that the Moral Majority boys campaign against abortion. I am angry when the same men who say, "Save OUR children" bellow "Build more and bigger bombers." That's right! Blast the children in other nations into eternity, or limbless misery as they lay crippled from "OUR" bombers! This does not jell."  Leonard Ravenhill
Comment

Found a good overview on it:
Originally posted by Mencius MoldbugOne new, and very popular (among the smart set) algorithmist automatism is Bayesianism. Bayesians are followers of Bayes' theorem, a result in probability theory. The Bayesians tend to congregate at the group blog Overcoming Bias, where they get together and figure out how many blue balls are in the white urn.
Here is a good intuitive explanation of Bayes' theorem by one prominent Bayesian. Please take my word for it: this level of hubris is not at all atypical. When they say things like "in cognitive science, Bayesian reasoner is the technically precise codeword that we use to mean rational mind," they really do mean it. Move over, Aristotle!
Of course, in Catholicism, Catholic is the technically precise codeword that they use to mean rational mind. I am not a Catholic or even a Christian, but frankly, I think that if I had to vote for a dictator of the world and the only information I had was whether the candidate was an orthodox Bayesian or an orthodox Catholic, I'd go with the latter.
Let's take a slightly closer look at Bayes' theorem, and see why these people are on crack.
Bayes' theorem is a pure product of mathematics. It is extremely true and extremely reasonable. If A and B are stochastic events, P(AB) really does equal P(A) * P(BA) / P(B).
The only problem is that this little formula is not a complete, dropin replacement for your brain. If a reservationist is skeptical of anything on God's green earth, it's people who want to replace his (or her) brain with a formula.
We can see this by looking for cases of cogitation for which Bayes' theorem is about as relevant as tits on a boar hog. Believe it or not, there turn out to be one or two such cases.
First, what Bayes' theorem gives us is a way of constructing one value from three others. We know: X = W * (Y/Z). Therefore, if we know W, Y, and Z, we can know X. Or if we know X, W and Z, we can know Y. And so on. Algebra! Do it yourself at home!
Now, there are certainly plenty of cases in which it is actually useful to calculate P(AB) from P(A), P(B) and P(BA). Spam filtering is one. P(Am) is the probability that message M is spam, P(Bs) is the probability that it contains some string S, P(BsAm) is the probability that if it's spam it contains S, and P(AmBs) is the probability that if it contains S it's spam. If we keep a database of past messages, we can estimate P(BsAm) and P(Bs) by assuming that spam messages are similar to other spam messages, and likewise for nonspam. Then we can construct P(Am) iteratively by starting with the percentage of all messages that are spam, and reapplying this algorithm for various S.
Note how interesting and special a case this is. It is precisely a case in which we have good estimates for Y and Z, and a crappy estimate for W which can be improved by iterating with a large set of Y's and Z's. Thus it makes sense to use Bayes' theorem.
But fundamentally, we are calculating one variable from three. The Rev. Bayes was a great man, no doubt, but his theorem does not contradict the Garbage Theorem. If there is garbage in W, Y or Z, there will be garbage in X. If we can iterate the computation for a wide variety of reliable Y and Z, we may be able to dilute the garbage in W to oblivion, but without reliable Y and Z, what we have is a magic box that turns garbage into fresh, tasty food.
To make this more concrete, let's look at how fragile Bayesian inference is in the presence of an attacker who's filtering our event stream. By throwing off P(B), any undetected pattern of correlation can completely foul the whole system. If the attacker, whenever he pulls a red ball out of the urn, puts it back and keeps pulling until he gets a blue ball, the Bayesian "rational mind" will conclude that the urn is entirely full of blue balls. And Bayesian inference certainly does not offer any suggestion that you should look at who's pulling balls out of the urn and see what he has up his sleeves.
Comment

Originally posted by KingsGambit View PostCould somebody point me in the direction of a good resource to learn the basics about Bayesian analysis, particularly as it may be applied to history? I'd like to be able to keep up here, mostly, and while I do know how to use Google , I figured I might need some help separating the wheat from the chaff.
You can check out here
http://commonsenseatheism.com/?p=13156
Its an explanation focusing more on giving you an intuitive understanding of Bayes.
he links to Yudkowsky's tutorial on lesswrong which is supposed to be good as well.
My introduction to Bayesian reasoning was in Swinburne's "The Existence of God". Its great in terms of methods.
Comment

If there is any worthwhile application in history, it's for cases in which plenty of statistical data is available for relevant and meaningful analysis.The greater number of laws . . . , the more thieves . . . there will be.  LaoTzu
[T]he truth I’m after and the truth never harmed anyone. What harms us is to persist in selfdeceit and ignorance — Marcus Aurelius, Meditations
Comment

Originally posted by Truthseeker View PostIf there is any worthwhile application in history, it's for cases in which plenty of statistical data is available for relevant and meaningful analysis.
Comment

Originally posted by Cerebrum123 View PostNot a fan of it eh?I'm not here anymore.
Comment

Originally posted by Carrikature View PostNot in this usage, no. Don't get me wrong, I don't have a problem with the theorem itself. My issue is with its application to the realm of apologetics and historicity. It looks like a working mathematical system being borrowed to imply some semblance of robust justification to a position one already holds. Neither side escapes this accusation.
Comment

Originally posted by Carrikature View PostNot in this usage, no. Don't get me wrong, I don't have a problem with the theorem itself. My issue is with its application to the realm of apologetics and historicity. It looks like a working mathematical system being borrowed to imply some semblance of robust justification to a position one already holds. Neither side escapes this accusation.
An Introduction to Probability Theory and Why Bayes’s Theorem is Unhelpful in History
Error in Bayes’s Theorem
Comment

Originally posted by Cerebrum123 View PostUndeerstood. I figured it was something like that.
Comment
Related Threads
Collapse
Topics  Statistics  Last Post  

Started by Starlight, 02262021, 05:38 PM

0 responses
19 views
0 likes

Last Post
by Starlight
02262021, 05:38 PM


Started by seer, 02162021, 09:31 AM

194 responses
907 views
0 likes

Last Post
by seer
Today, 07:15 AM


Started by rstrats, 02132021, 01:23 PM

27 responses
224 views
0 likes

Last Post
by rstrats
02262021, 10:08 AM


Started by seer, 02112021, 12:34 PM

103 responses
746 views
0 likes

Last Post
by seer
Today, 07:20 AM


Started by Starlight, 02082021, 03:38 AM

12 responses
116 views
0 likes

Last Post
by siam
02152021, 12:08 AM

Comment