Skewness of a probability distribution is a measure of its asymmetry; the higher the (absolute value of the) skewness, the more asymmetric the distribution.  Symmetric distributions have skewness of zero.  The formula for the skewness of a sample is: \[skewness\ =\ \frac{n}{\left(n\ -\ 1\right)\left(n\ -\ 2\right)}\frac{\sum_{i=1}^n \left(X_i\ –\ \bar X\right)^3}{s^3}\ ≈\ \frac1n\frac{\sum_{i=1}^n \left(X_i\ –\ \bar […]

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