96% of sex differences explained by statistical sampling

Whereas this is old news by now, it's still worth reminding everyone that according to Bilalic et al (2009), 96% of the difference in ranking between the 100 best male and 100 best female chess players in Germany can be explained by the fact that there are a 16:1 male - female ratio. The largest group will have larger variation in performance than the smaller group, i.e. just because more men play chess, the best - as well as the worst - players are expected to be men. That leaves only 4 % of the variation between the sexes to be explained by genes (G) and environment (E) and their interaction (G*E).

Without too much handwaving, this could be extended to other intellectual activities. Like science. The paper opens with a reference to Lawrence Summers (in)famous words back in 2005 and provides a simple statistical explanation for why Summers and many others should review their skills in basic statistics and include this among their hypotheses for why there are more male than female high ranked scientists.


Bilalic, Smallbone, McLeod and Gobet. Proc. R. Soc. B (2009) 276, 1161–1165. doi:10.1098/rspb.2008.1576

If you don't have access to Proc B, send me a gmail and I'll be happy to pass on a pdf of the paper.