October 11, 2009
Britain's Central Planning Death Panels
October 11, 2009
Free Market M.D.
October 11, 2009
Economies of Scale in Compliance
October 11, 2009
Balan's Challenge
October 10, 2009
The Pleasure of Telling Others What to Do
October 10, 2009
Gonick the Great - and How He Could Have Been Greater
October 9, 2009
More Scott Sumner
October 9, 2009
Not From The Onion
October 9, 2009
Thoughts on a Second Stimulus
McCloskey has always struck me as overly strident, yet I continue to read the most daft statistical analysis from even Ivy League business schools.
It seems likely to me that the problem is not so much a matter of confusion over the word "significant" as the inability of the vast majority of humans to understand the three door Monte Hall problem. When strikingly intelligent mathematicians can work it out but still not understand it, what hope is there for the rest of us.
Thanks for the posts on statistical significance. It's odd that some people ignore the fact that if you have enough data you can get statistical significance on just about anything. And why choose 95%? Most medical research works on 99%. Some like 90%? The choice depends on how much you want to prove your point.
And what if the p-value is .059? Technically it's not significant, but it's darn close!
As in other things, size matters!