Kurtosis In Statistics. This now becomes our basis for mesokurtic distributions. Kurtosis is a measure of the combined sizes of the two tails.
It is used to describe the extreme values in one versus the other tail. Kurtosis is useful in statistics for making inferences for example as to financial risks in an investment. Kurtosis is positive if the tails are heavier then for a normal distribution and negative if the tails are lighter than for a normal distribution.
The normal distribution is found to have a kurtosis of three.
Now that we have a way to calculate kurtosis we can compare the values obtained rather than shapes. Kurtosis is positive if the tails are heavier then for a normal distribution and negative if the tails are lighter than for a normal distribution. Excess kurtosis for normal distribution 3 3 0. It is actually the measure of outliers present in the distribution.
