Kurtosis Interpretation. If skewness is not close to zero then your data set is not normally distributed. The distribution has a lower and wider peak and thinner tails.
In other words kurtosis identifies whether the tails of a given distribution contain extreme values. When a set of approximately normal data is graphed via a histogram it shows a. For kurtosis extremely not normal dist.
The kurtosis is positive with a value greater than.
This greek word has the meaning arched or bulging making it an apt description of the concept known as kurtosis. For kurtosis extremely not normal dist. This greek word has the meaning arched or bulging making it an apt description of the concept known as kurtosis. Of course theaverage value of zis always zero but the average value ofz4is always 1 and is larger when you have afew big deviations on either side of the mean than when you have a lotof small ones.
