Beer-Drinking Scientist Debunks Productivity Correlation 130
austinpoet writes in with a blog post debunking the theory we discussed a few days back that scientists' beer consumption is linearly correlated with the quality of their work. Chris Mack, Gentleman Scientist and beer drinker, has analyzed the paper and found it is severely flawed. From his analysis: "The discovered linear relationship between beer consumption and scientific output had a correlation coefficient (R-squared) of only about 0.5 — not very high by my standards, though I suspect many biologists would be happy to get one that high in their work... Thus, the entire study came down to only one conclusion: the five worst ornithologists in the Czech Republic drank a lot of beer."
Hmm... do we need either of these studies? (Score:2, Informative)
Some alcohol is good ... to a point (Score:1, Informative)
Social drinking leads to better job performance and career success. http://www.ithaca.edu/ithacan/articles/0610/05/opinion/2drinking_.htm [ithaca.edu]
Excess alcohol consumption, on the other hand, is almost always a bad thing. There are some studies that show the benefit of moderate consumption but there is no studies that show that heavy consumption is anything but bad.
xkcd was there first (Score:2, Informative)
Re:xkcd was there first (Score:5, Informative)
"Ballmer peak" is, FYI, a joke [wikipedia.org] that's going over the heads of all you science-illiterate server monkeys.
R^2 = 0.5 Ain't Bad (Score:5, Informative)
As a comparison, 0.3 is pretty much the top end R-squared in personality psychology. that field is built on correlations that account for no more than 10% of the observed variance.
To combine the two, it's far more likely that TFA didn't actually measure beer drinking, but rather how much beer those scientists who drank beer would admit to drinking. Those who'll drink it are probably more likely to relax, which will make them more productive, and those who will admit it are less likely to fall prey to negative opinions of others, a major source of which is reviewers' comments on papers submitted for publication. Such comments are often undeservedly harsh, and in many cases coming from someone who doesn't know as much as the author about the topic. That can turn away those who place great store in the opinions of others, especially perceived authorities.
Next, on to Russia and WOTKA!
Re:Not only that (Score:3, Informative)
Re:Performance enhancing drugs (Score:5, Informative)
Also, the famous mathematician Paul Erdos [wikipedia.org] used amphetamines for this purpose:
-metric
Re:R^2 = 0.5 Ain't Bad (Score:3, Informative)
I agree with the first part, but not with the second. R^2 of
For example, sociability might be highly correlated with beer drinking and performance. There is likely to be a lot of "shared variance" between the two predictors, but it is possible that sociability alone would account for more variance in performance than beer drinking. An ANOVA (or equivalent) analysis would partition the variance between the variables and the variable-by-variable interactions.
* In the (US) financial markets, an important stat is how well a particular mutual fund correlates with the S&P 500. R^2 of less than
Re:We all know what to do now: (Score:4, Informative)
If by "american beer" you mean Bud/Miller/Coors. However there are hundreds of American micros that produce excellent beer in far more styles than you'll find in Europe. American beer is far from being limited to the mass produced light lager produced by the aforementioned major breweries.