Kurtosis Essential terms you should know.

Kurtosis A Term You Need to Know

Kurtosis is a measure of the tails of a data set or of the probability distribution of a random variable. It describes how the tails (extreme values) of the distribution deviate from the tails of a normal (bell-shaped) distribution. Excess Kurtosis can be either positive, negative, or zero. (Excess Kurtosis is calculated by subtracting 3 from the ordinary Kurtosis.)

A data set with positive excess kurtosis has a more extreme tails than a normal distribution, meaning that the tails of the distribution are longer. On the other hand, a data set with negative excess kurtosis has less extreme tails than a normal distribution. If the excess kurtosis of a data set is zero, it means that the tail character is the same as that of a normal distribution.

Kurtosis is an important factor to consider when analyzing a data set, as it can affect the interpretation of other statistical measures such as the mean and standard deviation. Kurtosis can also be used to identify outliers in a data set, as a high value of kurtosis may indicate the presence of outliers.

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