In the GSS, males report an average of 14.19, women an average of 4.76.* If you mean the median, then males report a median of 3, woman a median of 2.
In my statistics course, I use this as a classic example of biased statistics. Here is why I suspect bias.
Suppose that the number of men is M and the number of women is W. Suppose that an omniscient voyeur can count all of the heterosexual relationships. Call this number n. Then the average number of sex partners for men is n/M. For women, it is n/W. Assuming that W and M are about the same, then the omniscient voyeur will know that the averages are about the same. So if the reported averages are different, then the reported averages are biased statistics.
I believe this goes back to a logic joke that was rampant when I was in high school:
If all the boys are doing it and few, if any, of the girls are doing it, how is anything getting done?
I agree. There’s definitely either some overstating by the men, understating by the women, or a bit of both going on.
By definition, assuming the population sizes of both groups are equal (a reasonable assumption, I think) the mean averages also have to be equal. I find the most intuitive way to think about this is that any 1 additional coupling is simultaneously +1 to the total of the men as a group and +1 to the total of the women as a group. In your formulation this would be +1 to the value of n. If the denominators (population of both groups) are equal or approximately equal then so must be the means.
Bryan states that he’s excluding the 989 sexual partners and higher bin. It’s possible that there’s a small number of women with a huge number of male sexual partners (prostitutes) who are being excluded from this sample. If so, that could be the source of the disconnect.
“By definition, assuming the population sizes of both groups are equal (a reasonable assumption, I think) the mean averages also have to be equal. ”
I don’t agree with this. I’ll give a counter example: if each person was celibate except for their single marriage, and men married at 60 and women married at 20 and everyone lived to age 80, then the average adult female would have had 1 partner and the average adult male 0.33 partners.
Joe: “I don’t agree with this. I’ll give a counter example: if each person was celibate except for their single marriage, and men married at 60 and women married at 20 and everyone lived to age 80, then the average adult female would have had 1 partner and the average adult male 0.33 partners.”
In your example, wouldn’t you have to assume that there were a large discrepancy between the population sizes of the men and the women though? If everyone lives to age 80 and all the women marry at 20 and the men at 60, then at any particular point in time the number of women at age 20 must equal the number of men at age 60. In any case the demographics would have to be really skewed in one direction or the other for such an example to hold in the real world. I concede there are possibly some scenarios where the averages could be skewed very slightly, but I don’t think this would be the case for most data sets of this type.
May depend on how common ruffees are since this is from recall.