Descriptive Statistics Skewness And Kurtosis. Looking at S as representing a distribution the skewness of S is a measure of symmetry while kurtosis is a measure of peakedness of the data in S. Skewness and kurtosis are two commonly listed values when you run a softwares descriptive statistics function.
Descriptive Statistics Means and standard deviations should be given either in the text or in a table but not both. A symmetric distribution such as a normal distribution has a skewness of 0 and a distribution that is skewed to the left eg. These extremely high values can be explained by the heavy tails.
If the skewness of S is zero then the distribution represented by S is perfectly symmetric.
Oct 26 2020 skewness tells you the amount and direction of skewdeparture from horizontal symmetry and kurtosis tells you how tall and sharp the central peak is relative to a standard bell curve. For different limits of the two concepts they are assigned different categories. Kurtosis 3 describes the extremeness of the tails of a population distribution and is an indicator of data outliers. For a distribution with parameters for the mean sigma skewness and kurtosis I can only think of the Stable Levy distribution with its 4 parameters mean μ sd c skewness β and kurtosis α.
