I seek to learn through this site and others how to better my ability as a person and my skill at using my reason and understanding to best effect. I do fractal artwork as a hobby, and I'm working to develop it to professional levels, though I've a bit to go till I reach that degree of skill! This is a crazy world we're in, but maybe I can do a little, if only that, to make it a bit more sane than it otherwise would be.
Very hard to follow, this statistical analysis stuff. All I can say is the critiques of Bem seem to be more persuasive than the responses to the critiques. That’s not saying I know who’s right.
My own reaction is that the tests for psi seem to be pretty piss-poor: lots and lots and lots of wrong answers but because hits seem marginally better than chance, it’s a positive? Come on. Run trails against chance but also set up control tests where the results are 100% — but subjects don’t know that — and see what happens.
Bayes is perfect for this type of thing. If the prior probability is small (part of the numerator) and the probability that the hypothesis is not true is giant (part of the denominator), you end up with an extremely minute posterior probability. In other words, when the thing being proposed is “probably not true” then this analysis gives an appropriately small chance of it being true.
Your Eldritch Host
I'm a carbon-based bio-organism belonging to a particularly powerful and potentially self-destructive species native to a speck of dirt orbiting an average but temperamental yellow star in a backwater spiral arm of an insignificant galaxy.
Very hard to follow, this statistical analysis stuff. All I can say is the critiques of Bem seem to be more persuasive than the responses to the critiques. That’s not saying I know who’s right.
My own reaction is that the tests for psi seem to be pretty piss-poor: lots and lots and lots of wrong answers but because hits seem marginally better than chance, it’s a positive? Come on. Run trails against chance but also set up control tests where the results are 100% — but subjects don’t know that — and see what happens.
Bayes is perfect for this type of thing. If the prior probability is small (part of the numerator) and the probability that the hypothesis is not true is giant (part of the denominator), you end up with an extremely minute posterior probability. In other words, when the thing being proposed is “probably not true” then this analysis gives an appropriately small chance of it being true.