Do you have something on the difference between Traditional Rationality and Bayescraft?
I am finally taking Prob. & Stats next semester (and have not yet looked at the book to see how Bayes figures into it yet. I am going to be pissed if it doesn’t enter into the class at this point), so I figure that I will get my formal introduction to Bayes at that point. However, I do know the Basic P(A|B) = [ P(B|A) P(A) ] / P(B).
And, I can regurgitate Wikipedia’s entries on Bayes, yet I don’t seem to have any real context into which I can place the difference between Bayes and traditional Probability distributions… Can you help, please?
I am currently taking Stats(AP class in the USA, IB level elsewhere), and hope that I can help. A traditional probability test will take four frequencies(Male smokers, female smokers, male nonsmokers, and female nonsmokers) and tell you if there is a correlation with an X^2 test. Bayescraft lets you use gender as a way to predict the likelihood of smoking, or use smoking to predict gender.
The fundamental difference, as far as I can tell, is that Statistics takes results about samples and applies them to populations. Bayescraft takes results about priors and applies them to the future. The two use similar methodology to address fundamentally different questions.
Do you have something on the difference between Traditional Rationality and Bayescraft?
I am finally taking Prob. & Stats next semester (and have not yet looked at the book to see how Bayes figures into it yet. I am going to be pissed if it doesn’t enter into the class at this point), so I figure that I will get my formal introduction to Bayes at that point. However, I do know the Basic P(A|B) = [ P(B|A) P(A) ] / P(B).
And, I can regurgitate Wikipedia’s entries on Bayes, yet I don’t seem to have any real context into which I can place the difference between Bayes and traditional Probability distributions… Can you help, please?
Never let the official curriculum slow you down! But still approach things systematically, find yourself a textbook.
I am currently taking Stats(AP class in the USA, IB level elsewhere), and hope that I can help.
A traditional probability test will take four frequencies(Male smokers, female smokers, male nonsmokers, and female nonsmokers) and tell you if there is a correlation with an X^2 test.
Bayescraft lets you use gender as a way to predict the likelihood of smoking, or use smoking to predict gender. The fundamental difference, as far as I can tell, is that Statistics takes results about samples and applies them to populations. Bayescraft takes results about priors and applies them to the future. The two use similar methodology to address fundamentally different questions.