Skewness is defined as μ3 / σ3, where μ3 is the third moment about the mean and σ is the standard deviation. If Y is the sum of n independent random variables, all with the same distribution as X, then Skew[Y] = Skew[X] / √n. |
Skewness is defined as μ3 / σ3, where μ3 is the third moment about the mean and σ is the standard deviation. The skewness of a random variable X is sometimes denoted Skew[X]. |
If Y is the sum of n independent random variables, all with the same distribution as X, then it can be shown that Skew[Y] = Skew[X] / √n. |
Skewness is defined as μ3 / σ3, where μ3 is the third moment about the mean and σ is the standard deviation. The skewness of a random variable X is sometimes denoted Skew[X].
For a set of N values the skewness can be calculated as Σi(xi - μ)3 / Nσ3, where xi is the ith value and μ is the mean.
If Y is the sum of n independent random variables, all with the same distribution as X, then it can be shown that Skew[Y] = Skew[X] / √n.