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Kurtosis - Wikipedia.

Jan 14, 2019 · The formula used is μ 4 /σ 4 where μ 4 is Pearson’s fourth moment about the mean and sigma is the standard deviation. Excess Kurtosis Now that we have a way to calculate kurtosis, we can compare the values obtained rather than shapes. The kurtosis of a normal distribution equals 3. Therefore, the excess kurtosis is found using the formula below: Excess Kurtosis = Kurtosis – 3 Types of Kurtosis. The types of kurtosis are determined by the excess kurtosis of a particular distribution. The excess kurtosis can take positive or negative values, as well as values close to zero. 1. The standard measure of kurtosis, originating with Karl Pearson, is based on a scaled version of the fourth moment of the data or population. This number is related to the tails of the distribution, not its peak; hence, the sometimes-seen characterization as "peakedness" is mistaken.

Jun 21, 2011 · We know that the Mean gives us the central tendency of the data, the Standard Deviation explains the dispersion about the Mean, the Skewness represents the symmetry/asymmetry of the data, and the Kurtosis is related to the shape or peakedness characteristics. The kurtosis increases while the standard deviation stays the same, because more of the variation is due to extreme values. Moving from the normal distribution to the.