Negative Kurtosis Graph. Kurtosis quantifies whether the tails of the data distribution matches the gaussian distribution. The fatter part of the curve is on the right.
The kurtosis can be derived from the following formula. In terms of shape a platykurtic distribution has thinner tails examples of platykurtic distributions include the continuous and discrete uniform distributions and the raised cosine distribution the most platykurtic distribution of all is the bernoulli distribution with p 1 2 for. The solid line shows the normal distribution and the dotted line shows a distribution with a positive kurtosis value.
Outliers stretch the horizontal axis of the histogram graph which makes the bulk of the data appear in a narrow skinny vertical range thereby giving the skinniness of a leptokurtic distribution.
Notice that we define the excess kurtosis as kurtosis minus 3. Figure 1 examples of skewness and kurtosis. Distribution is shorter tails are thinner than the normal distribution. σ is the standard deviation bar x is the mean of the distribution.
