I simply can't imagine what relevant factor would cause a difference in the width of these curves. I know that, in general, men have a higher standard deviation for most activities and attributes than women, but these effects are minor. So, my question is, is there anything relating to the SD that you think affects the soundness of the underlying argument? If so, I'd actually be curious to learn more about it.
My argument here is simply the best reasoning I can muster given the data that I'm aware of. You are welcome to poke holes in the reasoning or present alternate data. I'm eager to learn more in either case.
"So, my question is, is there anything relating to the SD that you think affects the soundness of the underlying argument? "
What underlying argument? You are presenting a political position unsubstantiated by any facts. Arguing about the distribution of standard deviations about two imaginary curves is like arguing about something in Alice in Wonderland. (Note that i didn't make an argument either way about the std dev in my comment).
Speaking against political correctness will probably get me downvoted, but here goes anyway,
From your blog post, I gather you think "diversity" of genders/races makes better dev teams. All I am saying is "prove it". With data, not hypotheses.
I have yet to see any real evidence for this, whether in terms of sustained commercial success or even in a statistical sense.
Show us these supposed benefits from race/gender diversity as applied to software development and startups. Is that too much to ask?
So because you can't imagine it, it must not exist? Even though you can't imagine how the standard deviations could differ, the evidence of a difference is extremely strong.
And a 10% higher standard deviation is much less minor than you think if you are looking at an ability cutoff. If you have two populations of equal size with equal medians, one of which has a 10% higher standard deviation, then about 99.5% of the top 1% across both groups belongs to the group with the higher standard deviation. It is that extreme because the standard bell curve has tails that drop off very rapidly, so one curve has pretty much ended while the other curve is still going on.
No, not really. Why? Which bit of statistical theory tells you this would be the case?
"I'm not aware of any data to suggest otherwise."
Well you don't have any data going the other way either do you?