Kurtosis


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Kurtosis

Measures the fatness of the tails of a probability distribution. A fat-tailed distribution has higher-than-normal chances of a big positive or negative realization. Kurtosis should not be confused with skewness, which measures the fatness of one tail. Kurtosis is sometimes referred to as the volatility of volatility.
References in periodicals archive ?
0124 for each n; moreover, the simulated skewness and kurtosis values are very close to 0.
For the explanatory variables, Panels A and B show that the skewness and kurtosis values of advertising, R&D and control variables are skewed and have excess kurtosis.
A problem with the original items was a great degree of kurtosis and skewness.
Measures of multivariate skewness and kurtosis with applications.
fits a bell-shaped curve, with the mean defining the location of the distribution, and standard deviation defining the dispersion of the distribution; zero skewness which measures symmetry, and zero kurtosis which measures the distribution in the tails of the distribution).
In tables 4 and 5 we can observe that for both subsamples: (i) the values of the mean and of the median are close to each other for all the dimensions of emotional competence; (ii) the minimum and the maximum values are at great distance one from another; and (iii) the coefficients of asymmetry and kurtosis are mostly inferior to 1.
Skewness and kurtosis indicate the symmetry and the clustering of data towards the center of a distribution.
Keywords: vibration analysis, spectrometry, centrifuge pomp, kurtosis and fault diagnostics
The normal distribution has an excess kurtosis of 0 but the distribution of home runs has an excess kurtosis of 13.
Of the tests used, PSI, SDQ, HADS (anxiety) and DBSES were normally distributed, whereas HADS (depression) was not and was positively skewed with some evidence of kurtosis.
A common rule-of-thumb test for normality is to divide item skewness and kurtosis statistics by their standard errors.
Kurtosis (Rku): the measure of the peak-ed-ness of the profile about the mean line.