High Kurtosis Graph. Compared to a normal distribution its tails are shorter and thinner and often its central peak is lower and broader. This is exactly what is depicted in graph c.
The leptokurtic distribution shows heavy tails on either side indicating large outliers. A high kurtosis is more often caused by processes that directly contribute to a high peak than by processes that directly contribute to fat tails. For example data that follow a t distribution have a positive kurtosis value.
Where the probability mass is concentrated around the mean and the data generating process produces occasional values far from the mean where the probability mass is concentrated in the tails of the distribution.
The excess kurtosis is defined as kurtosis minus 3. Compared to a normal distribution its tails are shorter and thinner and often its central peak is lower and broader. Leptokurtic indicates a positive excess kurtosis. The graph below describes the three cases of skewness.
