

TechCrunch messes up the math on sexism - yummyfajitas
http://crazybear.posterous.com/techcrunch-messes-up-the-math-on-sexism

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luchak
The lengths to which this article goes to construct a model sympathetic to the
author's views are incredible. It takes data showing a greater variance among
males than females:

\- in mathematical ability

\- among schoolchildren

\- on a standardized test

and generalizes them to:

\- many different types of abilities

\- among the Y Combinator applicant pool

\- on the Y Combinator application process

Not only that, but by its end, the article is postulating a model in which
literally one in a million people have sufficient aptitude to be accepted by Y
Combinator - whether they're interested in it or not!

Even if you grant the author all of those assumptions, plus the risk aversion
thing, you're only down to 13% women, three times what TechCrunch says Y
Combinator actually accepts. I guess you could add another independent 99.9th
percentile ability requirement, but then you're talking about one in a
_billion_ people being Y Combinator worthy. Or you could try to find a
different, more tilted risk aversion statistic -- but at that point I think
we'd be cherry-picking citations to fit a conclusion.

So, sure, if you accept a whole raft of dubious assumptions, you can explain
the 4% acceptance rate by aptitude alone. But enough dubious assumptions can
explain almost anything.

~~~
yummyfajitas
_Not only that, but by its end, the article is postulating a model in which
literally one in a million people have sufficient aptitude to be accepted by Y
Combinator - whether they're interested in it or not!_

Why do you feel this is unreasonable? Do you think there is some huge pool of
people good enough for YC who just don't get in? Maybe the true numbers are 1
in 100,000, but I'd be surprised if they are much higher than that.

In any case, I'm not attempting to claim my assumptions are correct. The only
point I'm making is that small differences in underlying probability
distributions can have large effects in the composition of people accepted
into a _highly selective_ program.

I.e., Eric Ries is making the fallacy of the excluded middle: "either
aptitude/preference differences are huge, or else they don't explain much."
This is simply mathematically incorrect.

~~~
Mz
I thought you had a point. Professional basketball comes to mind, where it's
incredibly unusual for someone to be of "normal" height. A height difference
gives you an advantage which I suspect creates a positive feedback loop
(advantage leads to more enjoyment, which leads to more practice...etc) and
remains a significant factor even when all other things are equal (like innate
talent).

~~~
luchak
_advantage leads to more enjoyment, which leads to more practice...etc_

I actually agree with you here. This is why I think things like
sexist/marginalizing presentations at conferences are a big deal: a hostile
environment seems to me a lot more likely to achieve this than possible
differences at the bare fringe of the aptitude spectrum.

~~~
Mz
FWIW: I'm female and I'm very aware of the chill effect when, say, in an
online forum some guy says something hostile about women/a woman and gets a
group high five out of it (massively upvoted and that kind of thing). In such
cases, it is not uncommon for me to feel like saying something like "there's
some truth to that but there's another side to that story as well" only it's
obvious that the other side is not welcome information and trying to present
it won't accomplish anything constructive. In other words, I am keenly aware
that if it were a neutral, not emotionally charged discussion, I have
additional information which might cast light on the subject for the guys and
might even be helpful to them but there is no hope of being heard, so I keep
my mouth shut rather than borrow trouble. And I'm a rather loud mouthed brassy
broad, so I'm sure the chill effect has an even stronger ability to keep your
typical woman quiet.

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davidcann
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.

~~~
zacharypinter
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.

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lomegor
I'm not sure if this article is trying to say that those small differences
account for the differences between the percentage of men and women in YC, or
if it's just disproving the mathematical aspect of the TechCrunch article.

I'm not saying either of those articles is right, but clearly none have shown
why that difference exist.

------
Mz
Does anyone know the two following stats:

What percentage of _applicants_ to YC are female?

Acceptance rate in terms of applicant pool for each gender? (ie "10% of all
male applicants are accepted vs 14% of all female applicants" -- and I chose
to skew it that way intentionally because I am betting if there is a gender
based selection bias it is probably in that direction)

These statistical analyses are meaningless outside of that context. If it just
so happens that only 4% of the applicants are female, then why should the
gender balance of final selections be any different from that?

