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Kurtosis is a statistical term that describes the degree to which scores cluster in a frequency distribution's tails or peak. The peak of the distribution is the highest point, and the tails are the lowest points. Kurtosis is divided into three types: mesokurtic, leptokurtic, and platykurtic.

Kurtosis has been used in many fields, including finance, economics, engineering, and science. In particular, it has been applied in quantitative finance and economics to determine market risk factors such as volatility and excess kurtosis (excess kurtosis refers to the degree of variability around the mean).

Kurtosis is a measure of the degree to which a set of numbers is dispersed or peaked. It can be calculated from the standard deviation and the mean.

Kurtosis is a measure of how far the values in a data set are from the normal distribution. It is often used to assess how extreme or peaked a distribution is.

The degree of lopsidedness in the frequency distribution is measured by skewness. Kurtosis, on the other hand, is a measure of the frequency distribution's degree of tailedness. Skewness indicates a lack of symmetry, i.e., the curve's left and right sides are unequal in relation to the central point.

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