Understanding Kurtosis. Jun 06 2018 Kurtosis. Kurtosis is a measure of whether the data are heavy-tailed profusion of outliers or light-tailed lack of outliers relative to a normal distribution.
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The tails of a. And one is skewness and the other is kurtosis. If the bulk of the data is at the left and the right tail is longer we say that the distribution is skewed right or positively.
A correlation between kurtosis and skewness might also be important so that not all combinations of values for theses parameters are possible further complicating the whole story the region of.
If the bulk of the data is at the left and the right tail is longer we say that the distribution is skewed right or positively. It is sometimes referred to as the volatility of volatility. Jun 06 2018 Kurtosis. Kurtosis on the other hand refers to the pointedness of a peak in the distribution curveThe main difference between skewness and kurtosis is that the former talks of the degree of symmetry.
