Yes, at the UnivariateStatistic level, these would need to be new classes. My question as well is "Does it apply as well to higher order moments?"
In theory, yes, though I have never seen non-bias-corrected versions of Skewness and Kurtosis used. The current formulas are all defined for the most common use case where the data represent a sample from a population whose true distribution and associated parameters are unknown.population The formulas that we use provide unbiased estimators for population parameters in this case. This is explained fairly well for the Variance here:
http://mathworld.wolfram.com/Variance.html
and for Skewness and Kurtosis here:
http://mathworld.wolfram.com/k-Statistic.html
The "Population Variance" is useful when the data *are* the population (i.e. the distribution is discrete and there is no sampling going on). I am not aware of use cases where Skewness and Kurtosis are useful in analyzing full population data or other uses for the non-bias-corrected versions of these. These could exist, I am just not aware of them.
Maybe we should place everything into the following packages:
I don't think we need yet another subpackage.
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