What Is Kurtosis

In probability theory and statistics kurtosis from greek. The minus 3 at the end of this formula is often explained as a correction to make the kurtosis of the normal distribution equal to zero as the kurtosis is 3 for a normal distribution. Kurtosis is an important descriptive statistic of data distribution.

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Kurtosis is a statistical measure that defines how heavily the tails of a distribution differ from the tails of a normal distribution.

What is kurtosis. κυρτός kyrtos or kurtos meaning curved arching is a measure of the tailedness of the probability distribution of a real valued random variable. It tells us the extent to which the distribution is more or less outlier prone heavier or light tailed than the normal distribution. The value is often compared to the kurtosis of the normal distribution which is equal to 3. In other words kurtosis identifies whether the tails of a given distribution contain extreme values.

Three different types of curves courtesy of investopedia are shown as follows. The degree of tailedness of a distribution is measured by kurtosis. Kurtosis tells you the height and sharpness of the central peak relative to that of a standard bell curve. That is data sets with high kurtosis tend to have heavy tails or outliers.

When a set of approximately normal data is graphed via a histogram it shows a. Mesokurtic leptokurtic and platykurtic. The peak is the tallest part of the distribution and the tails are the ends of the distribution. Here x is the sample mean.

Kurtosis is a measure of whether the data are heavy tailed or light tailed relative to a normal distribution. Kurtosis is the measure of the thickness or heaviness of the tails of a distribution. Kurtosis is a measure of the combined weight of a distribution s tails relative to the center of the distribution. If the kurtosis is greater than 3 then the dataset has heavier tails than a normal distribution more in the tails.

It measures the amount of probability in the tails. There are three types of kurtosis. The kurtosis of a distribution is in one of three categories of classification. Kurtosis is a measure of the combined sizes of the two tails.

Data sets with low kurtosis tend to have light tails or lack of outliers. Kurtosis is a statistical measure used to describe the degree to which scores cluster in the tails or the peak of a frequency distribution.