Here are a few quantitative questions which would help us get closer to the truth:
What % of the applicant pool was women?
What % of the potentially qualified applicant pool was women? [1]
How many interns were hired? [2]
Are there any objective numbers (i.e., besides the # hired) to suggest that a large fraction of the most qualified people were women?
[1] These numbers can allow us to do the same calculation I did here (http://news.ycombinator.com/item?id=5233153), or even a proper Bayesian probability update.
[2] I.e., if 3 interns were hired, this is a tempest in a teapot caused by a statistical fluke.
Here are a few quantitative questions which would help us get closer to the truth:
What % of the applicant pool was women?
What % of the potentially qualified applicant pool was women? [1]
How many interns were hired? [2]
Are there any objective numbers (i.e., besides the # hired) to suggest that a large fraction of the most qualified people were women?
[1] These numbers can allow us to do the same calculation I did here (http://news.ycombinator.com/item?id=5233153), or even a proper Bayesian probability update.
[2] I.e., if 3 interns were hired, this is a tempest in a teapot caused by a statistical fluke.