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 […]

**This article is for members only. You can become a member now by purchasing a**

**CFA® Level I Quantitative Methods Membership, CFA® Level I Membership**

**This will give you access to this and all other articles at that membership level.
**