Estimating third central moment C3 for privacy case under interval and fuzzy uncertainty
نویسندگان
چکیده
Some probability distributions (e.g., Gaussian) are symmetric, some (e.g., lognormal) are non-symmetric (skewed). How can we gauge the skeweness? For symmetric distributions, the third central moment C3 def = E[(x − E(x))] is equal to 0; thus, this moment is used to characterize skewness. This moment is usually estimated, based on the observed (sample) values x1, . . . , xn, as C3 = 1 n · n ∑ i=1 (xi − E), where E def = 1 n · n ∑
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