I’ve still not gotten around to reading the actual paper, but slashdot today mentioned some additional analysis of the paper correlating increase beer drinking with reduced scientific success (measured in terms of publications and citations). My initial thought after reading the first of many posts about this that appeared around the internet was as follows:correlation != causationThis blog post points out some additional issues with the paper, which I’ll now have to check out, given that it is both short, and to evaluate the other scientist’s analysis.Beyond the correlation != causation, the author of the blog post points out that there are really only 34 data points, and without 5 of them the correlation falls apart. Additionally, the R-squared for correlation is 0.5. In addition to the comment made pointing out that an equally probable explanation for the data was that low-output scientists were drinking more, there’s also that statistic itself. An R-squared of 0.5 suggests that 50 percent of the variation in output can be attributed to beer drinking level. That still leaves a large percentage of potential other influences on top of alternate causal relationships.Ah well, I suppose the original article may have aimed more at headlines or amusement, but it’s still fun to try and justify beer. I think the common sense on this item is likely close to the mark: heavy drinking certainly doesn’t help with your output, but reasonable social drinking probably doesn’t correlate well with output levels.