Skewness And Kurtosis Meaning. Govern the kurtosis effect far more than the values near the mean peak. If skewness is not close to zero then your data set is not normally distributed.
With the help of skewness one can identify the shape of the distribution of data. Two distributions may have the same mean and standard deviation but may differ in their shape of the distribution. Skewness moments and kurtosis introduction the measures of central tendency and variation discussed in previous chapters do not reveal the entire story about a frequency distribution.
Skewness kurtosis simplified.
Use kurtosis to help you initially understand general characteristics about the distribution of your data. Kurtosis value of 0. The main difference between skewness and kurtosis is that the former talks of the degree of symmetry whereas the latter talks of the degree of peakedness in the frequency distribution. Whereas skewness measures symmetry in a distribution kurtosis measures the heaviness of the tails or the peakedness.
