Contents
- Index
Skewness
The third moment of a distribution and the first shape parameter. The skewness is measure of the symmetry of the distribution. A skewness of zero means the distribution is symmetrical like the normal distribution shown below:
A positive skewness means the upper tail is longer than the lower tail like the Largest Extreme Value distribution with a skewness of 1.14 shown below:
A negative skewness means the lower tail is longer than the upper tail like the Smallest Extreme Value distribution with a skewness of -1.14 shown below:
A skewness value of 1 and above or -1 and below represents a sizable departure from normality. The formula used for estimating the skewness from a set of data is:
where n is the sample size, 
represents the data points, 
is the average and S is the standard deviation.