We have already discussed normal distribution. Do you remember the bell-shaped graph? If not, just check out the first section of this chapter again. You may well ask yourself, why should you remember that? It is necessary in order to understand the concept of kurtosis. Basically, kurtosis is a statistical measure that illustrates how heavily the tails of distribution differ from those of a normal distribution. This technique can identify whether a given distribution contains extreme values. 

Kurtosis, unlike skewness, is not about the peakedness or flatness. It is the measure of outlier presence in a given distribution. Both high and low kurtosis are an indicator that data needs further investigation. The higher the kurtosis, the higher the outliers.