Plausible for a given individual, but quite an outlier from the average man or woman, I’d expect. Even so, though, how many of her partners also had 10-20 partners per year? If few of them, this survey, if she and all her partners filled it out, would skew heavily female in question one. I don’t think we can rule out the idea that question one is likely to produce very different results for male and female, even if everyone answered truthfully. It’s not immediately implausible, at least, as you imply.
Differences in question one are not only implausible, they’re impossible.
If such extreme female outliers really existed, at least some surveys would show number of partners for women being massively higher than for men, just by including one such person by chance. There’s no statistical way around it, unless you postulate 1 in 100,000 female outliers with millions of distinct male partners each, what’s quite ridiculous.
And we have pretty good evidence that women lie anyway.
If such extreme female outliers really existed, at least some surveys would show number of partners for women being massively higher than for men, just by including one such person by chance. There’s no statistical way around it
The survey methodology could systematically fail to include outliers. That is the prostitute theory of the discrepancy, not just that there are female outliers, but that there is a reason that they aren’t sampled. “There’s no statistical way around it”
if the samples are not biased.
I just showed how it isn’t impossible. Further, while you apparently assume that I meant only that women could have more partners on average than men, I didn’t imply that the actual survey would skew either way (on average), only that we have an example of where it would skew female.
I think it might actually be the case, in at least some societies, that fewer men than women have sex at all, on average, due to men who can have sex at all having sex with several or many women each. That’s an example of how it could easily skew male on question one, and I don’t really get how you believe that it’s impossible to have a higher population of one sex than the other that doesn’t have sex at all. It seems likely that there would be at least some difference.
If such extreme female outliers really existed, at least some surveys would show number of partners for women being massively higher than for men, just by including one such person by chance.
But don’t surveys generally throw out outlier responses?
Define outlier. I have thrown out, or capped, data that is logically impossible, but I’ve also knowingly, and unknowingly included outliers I was skeptical of because there is no widely agreed upon standard for treating them. I could try many different standards/assumptions, and see if they affect my analysis but this type of work is time consuming and would not be of less interest to my colleagues than the work I would have to sacrifice. I realize this is sometimes problematic and I will make some effort to shift the standards in my discipline, sociology.
It would be a stupid thing to do. In any case that 48-nation survey mentioned throwing away highest 1% of male responses, as supposed outliers, and nothing about throwing away any female responses, which is extremely incompatible with “female outliers” theory.
Plausible for a given individual, but quite an outlier from the average man or woman, I’d expect. Even so, though, how many of her partners also had 10-20 partners per year? If few of them, this survey, if she and all her partners filled it out, would skew heavily female in question one. I don’t think we can rule out the idea that question one is likely to produce very different results for male and female, even if everyone answered truthfully. It’s not immediately implausible, at least, as you imply.
Differences in question one are not only implausible, they’re impossible.
If such extreme female outliers really existed, at least some surveys would show number of partners for women being massively higher than for men, just by including one such person by chance. There’s no statistical way around it, unless you postulate 1 in 100,000 female outliers with millions of distinct male partners each, what’s quite ridiculous.
And we have pretty good evidence that women lie anyway.
The survey methodology could systematically fail to include outliers. That is the prostitute theory of the discrepancy, not just that there are female outliers, but that there is a reason that they aren’t sampled. “There’s no statistical way around it” if the samples are not biased.
...
I just showed how it isn’t impossible. Further, while you apparently assume that I meant only that women could have more partners on average than men, I didn’t imply that the actual survey would skew either way (on average), only that we have an example of where it would skew female.
I think it might actually be the case, in at least some societies, that fewer men than women have sex at all, on average, due to men who can have sex at all having sex with several or many women each. That’s an example of how it could easily skew male on question one, and I don’t really get how you believe that it’s impossible to have a higher population of one sex than the other that doesn’t have sex at all. It seems likely that there would be at least some difference.
But don’t surveys generally throw out outlier responses?
Define outlier. I have thrown out, or capped, data that is logically impossible, but I’ve also knowingly, and unknowingly included outliers I was skeptical of because there is no widely agreed upon standard for treating them. I could try many different standards/assumptions, and see if they affect my analysis but this type of work is time consuming and would not be of less interest to my colleagues than the work I would have to sacrifice. I realize this is sometimes problematic and I will make some effort to shift the standards in my discipline, sociology.
It would be a stupid thing to do. In any case that 48-nation survey mentioned throwing away highest 1% of male responses, as supposed outliers, and nothing about throwing away any female responses, which is extremely incompatible with “female outliers” theory.