Comparison of means is useless in this instance

Here's a tweet that I happened upon:

The graph is available here. The idea of the graph appears to be that the average 2012 science scores on the PISA test were similar for boys and girls, so the percentage of women should be similar to the percentage of men among university science graduates in 2010.

The graph would be more compelling if STEM workers were drawn equally from the left half and the right half of the bell curve of science and math ability. But that's probably not what happens. It's more likely that college graduates who work in STEM fields have on average more science and math ability than the average person. If that's true, then it is not a good idea to compare average PISA scores for boys and girls in this case; it would be a better idea to compare PISA scores for boys and girls in the right tail of science and math ability because that is where the bulk of STEM workers likely come from.

Stoet and Geary 2013 reported on sex distributions in the right tail of math ability on the PISA:

For the 33 countries that participated in all four of the PISA assessments (i.e., 2000, 2003, 2006, and 2009), a ratio of 1.7–1.9:1 [in mathematics performance] was found for students achieving above the 95th percentile, and a 2.3–2.7:1 ratio for students scoring above the 99th percentile.

So there is a substantial sex difference in mathematics scores to the advantage of boys in the PISA data. There is also a substantial sex difference in reading scores to the advantage of girls in the PISA data, but reading ability is less useful than math ability for success in most or all STEM fields.

There is a smaller advantage for boys over girls in the right tail of science scores on the 2012 PISA, according to this report:

Across OECD countries, 9.3% of boys are top performers in science (performing at Level 5 or 6), but only 7.4% of girls are.

I'm not sure what percentile a Level 5 or 6 score is equivalent to. I'm also not sure whether math scores or science scores are more predictive for future science careers. But I am sure that it's better to examine right tail distributions than mean distributions for understanding representation in STEM.

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