Women "Advertise" Fertility
Dik Zak writes with word of a paper published in the journal Hormones and Behavior. A study found that women take greater care over their appearance when they are at peak levels of monthly fertility. The researchers took two photos of each of 30 women, one near ovulation and one at the other end of her cycle. They then showed the paired photos (with faces obscured) to a group of observers, who were asked to judge in which photo the women were trying to look more attractive. The observers chose the "high fertility" subject nearly 60% more of the time than would be expected by chance.
Hardly statistically significant:-
60% of 30 is 18 - I mean come on, that's only 3 over the pure chance 50%!
The case study was to small, only 30 women with only 2 pictures, not only did we not collect data, but with the lack of numbers we creates a very large error of margin.
Example, flip a coin once, and you get heads, your test reveals 100% heads when flipping a coin. Flip it 10 times, you got heads 3 times, so according to this test when flipping a coin you have 30% chance to get heads. Now flip it 100 times. That number will be a lot closer to 50%.
Try 1000 women with 6 pictures each (3 in prime and 3 out of prime) then have 100 different people scoring each card.
All this test does is shows is hey maybe there is something, and let us do a real test.
The spirit of resistance to government is so valuable on certain occasions that I wish it to be always kept alive
You'd better be careful saying things like this around here, some slashbot will crop up and tell you that for lots of people on this thing, it isn't their first language.
Frankly I think that if someone wants to participate in a discussion in a given language, they should do all they can to master it, which is why I haven't moved someplace tropical yet... I feel a responsibility to speak the local language. I only wish more people in the USA felt that way...
"You're right," Fisheye says. "I should have set it on 'whip' or 'chop.'"
> I've seen studies with meaningful results in as few as 8 samples.
I don't think you have.
> Nevertheless, this particular study had 1260 samples. 42 guessers * 30 guesses each. More than a
> thousand samples is plenty for significance.
The important number here is 42. You could ask 2 people to guess 1,000,000 times. That's 2,000,000 samples. That's plenty, right?
-GiH