Skewness is a measure of the asymmetry of the distribution of a real-valued
random variable. Roughly speaking, a distribution has positive skew if the asymmetry is towards the positive direction, and negative skew if it is towards the negative direction (i.e., positive skew if the positive tail is longer and negative skew if the negative tail is longer).
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.
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.