Skewness and Kurtosis

Skewness and kurtosis describe the symmetry and shape of the distribution of values in a dataset. Skewness describes symmetry; a dataset is symmetric if it looks the same to the left and right of the centre and is skewed if the left and right sides are different. A perfectly symmetrical dataset has a skewness of zero.

Kurtosis describes how peaked or flat the dataset is relative to a standard normal distribution. The application calculates excess kurtosis, in which a peaked distribution has a negative value and a flat distribution has a positive value. A perfectly normal distribution has an excess kurtosis of zero.