BRYAN CAPLAN
May 7, 2013
Keynesian Bets: What's Out There
May 6, 2013
Keynesian Bets Bleg
May 6, 2013
The Pyramid of Macroeconomic Insight and Virtue
May 2, 2013
A Natalist Provision
May 1, 2013
I Was a Teenage Misanthrope
DAVID HENDERSON
May 5, 2013
John Thacker on Vaccinations and the Sequester
May 3, 2013
Chef Rudy's Virtues Project
May 2, 2013
My take on Reinhart and Rogoff
May 1, 2013
Medicare Kills a Program


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!