ARNOLD KLING
August 14, 2011
The Top Political Contributors
August 11, 2011
Gender and the New Commanding Heights
August 11, 2011
Jamie Galbraith Makes an Assumption
August 11, 2011
Macroeconometrics: The Science of Hubris
August 10, 2011
Real and Nominal Bond Yields
BRYAN CAPLAN
August 14, 2011
The Effect of Thumb Sucking on Income
August 12, 2011
The Voice of Cold, Hard Truth to All Would-Be Educators
August 12, 2011
Ability, Morality, and Prosperity: A Paper and a Report
August 11, 2011
The Theory of Time and Frittering
August 10, 2011
Male Variance and the Remnants of the Gender Gap
DAVID HENDERSON
August 9, 2011
Hayek in "Unbroken", Part Two
August 8, 2011
Hayek in "Unbroken"
August 5, 2011
James Bovard on the Peace Corps
August 4, 2011
Summers Way Off on FDR and 1941
August 3, 2011
The "Amazon" Tax
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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!