Skewness And Kurtosis In Statistics. For different limits of the two concepts they are assigned different categories. Maths guide now available on google play.
It is actually the measure of outliers present in the distribution. So we can conclude from the above discussions that the horizontal push or pull distortion of a normal distribution curve gets captured by the skewness measure and the vertical push or pull distortion gets captured by the kurtosis measure. Skewness is a measure of the symmetry in a distribution.
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.
Now let s look at the definitions of these numerical measures. If the skewness of s is zero then the distribution represented by s is perfectly symmetric. Statistically two numerical measures of shape skewness and excess kurtosis can be used to test for normality. Video explaining what is skewness and the measures of skewness.
