But, AP - there is significant uncertainty above or below the average. Unless a sample is badly skewed, the peak of the curve will coincide broadly with the average, and there will "outliers" either side of the central point representing the natural variation in the population. In the case of the example you provide, the "outliers" are some 30 grammes either side of the average for both males and females - which means a total "window" of 60 grammes. This amount of variation is vastly greater than the trifiling 10 gramme difference between the male and female averages. This further implies that there is a large degree of overlap between the two genders in terms of kidney weight, and hence a significant margin for error.
It is precisely the same with other bodily characteristics - yes, there are averages, but there is a large amount of variation either side of those averages within both sexes, and there is a large degree of overlap. One can no more state that "a kidney weighs X grammes, therefore it came from a woman", than one can say that "a person is six feet high, therefore that person must be a man". It's as simple as that.
It is precisely the same with other bodily characteristics - yes, there are averages, but there is a large amount of variation either side of those averages within both sexes, and there is a large degree of overlap. One can no more state that "a kidney weighs X grammes, therefore it came from a woman", than one can say that "a person is six feet high, therefore that person must be a man". It's as simple as that.
Comment