He's a damn frequentist! (the big issue is that he's not a philosopher, not that there's anything wrong with it....)
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To understand a lot of statistical ideas, you need to know about
probability. The two fields are inextricably entwined: sampled statistics
works because of probabilistic properties of populations.
I approach writing about probability with no small amount of trepidation.
My latest book project has been coediting the proceedings of the 2013 MOVES Conference held in New York City, which has turned out to be a lot harder than I anticipated.
Marilyn Mann pointed me to an interesting post by David Rind over at Evidence in Medicine (thanks!).
The first key concept in probability is called a random variable.
Random variables are a key concept - but since they're a key concept of the
frequentist school, they are alas, one of the things that bring out more of
I was happy to know nothing about the issue:)
They bayesians and frequentists are bashing each other? Still?
Well, ÐС-С seems to be incorrect in his interpretation of the misuse.
bayesian approach seems to be pretty close to our mind:)
It's not one of those misleading and hard to handle approaches.
If we didn't understand the 'information' concept - there would be no bayesian thinking. It is nearly innate.
Does ability to count provocate mistakes like '2+3=6'?
So, i believe, it rather makes some of the mistakes we make clear and M C-C may thank mr. Bayes for this. (instead of blaming)
Unfortunately, statistics in general IS one of those misleading instruments.:(((( Alas. Where i find the calculus or the set theories bright, beautiful and clear things - i feel myself like pressing the round head into square hat while trying to understand statistics.
BTW, underlying philosophy - is the thing we have to understand rather than clash over and fight for:)
I disagree with the idea of looking for the weak sides of everithing. There are the things just to understand:) What are the weakntsses of the crow?
So yes, damned frequentist!
PS. Statistics usually is OK in population genetics, of course.
I mean the obvious thing - its ability to mislead depends on objects it's applied to and the questions you ask.