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I would think that math aptitude has very little to do with developing great products and companies, so I don't understand this argument. It doesn't even have

I would think that math aptitude has very little to do with developing great products and companies, so I don't understand this argument. It doesn't even have much to do with many types of programming.

deleted 15y ago
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yummyfajitas 15y ago
From the article: "I'm not attempting to claim science currently knows everything about this topic. The only point I'm making is that it does not take "really extreme" differences in aptitude or innate preferences to account for gender differences in high end professions." This is a counterpoint to Eric Ries, who claims: "Here in Silicon Valley, we’re looking for the absolute best and brightest, the people far out on the tail end of aptitude...How far apart would the two populations have to be to explain YC’s historical admission rate of 4% women? It would have to be really extreme." The only point is to do the math and demonstrate that small differences can add up to a lot if you have highly selective filters. I chose mathematical ability as an example because a) it's fairly well studied and b) Eric Ries cites a slideshare presentation which also uses it as an example. (However, the data used in the presentation are about 20 years older than mine.)
zacharypinter 15y ago
Whether it's math aptitude or an aptitude in some other tangentially related field, I think the idea is that men in general tend to have more variance in their distribution, though the mean ends up being about the same. "Small differences in the distributions of men and women don't allow you to predict much about any individual trait of a randomly selected individual. But when you limit yourself to the far tails of probability distributions, they do. " So, he's saying that by being more selective for a field that men have greater variance in, you're more likely to find more men at the far tails.

deleted 15y ago

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yummyfajitas 15y ago

From the article: "I'm not attempting to claim science currently knows everything about this topic. The only point I'm making is that it does not take "really extreme" differences in aptitude or innate preferences to account for gender differences in high end professions." This is a counterpoint to Eric Ries, who claims: "Here in Silicon Valley, we’re looking for the absolute best and brightest, the people far out on the tail end of aptitude...How far apart would the two populations have to be to explain YC’s historical admission rate of 4% women? It would have to be really extreme." The only point is to do the math and demonstrate that small differences can add up to a lot if you have highly selective filters. I chose mathematical ability as an example because a) it's fairly well studied and b) Eric Ries cites a slideshare presentation which also uses it as an example. (However, the data used in the presentation are about 20 years older than mine.)

zacharypinter 15y ago

Whether it's math aptitude or an aptitude in some other tangentially related field, I think the idea is that men in general tend to have more variance in their distribution, though the mean ends up being about the same. "Small differences in the distributions of men and women don't allow you to predict much about any individual trait of a randomly selected individual. But when you limit yourself to the far tails of probability distributions, they do. " So, he's saying that by being more selective for a field that men have greater variance in, you're more likely to find more men at the far tails.