Respuesta :
The normality of a distribution as well as how fateful its tails are Kurtosis is a test for a distribution's normality that focuses on the size of the tails.
Kurtosis is a metric that indicates how heavy-tailed or light-tailed the data are in comparison to a normal distribution. In other words, data sets with a high kurtosis tend to have large outliers or heavy tails. Data sets with low kurtosis frequently lack outliers and have light tails. The worst-case scenario would be a uniform distribution.
Kurtosis is three and skewness is zero for the normal distribution. The test is based on how much the data's skewness deviates from zero and how far its kurtosis deviates from three. When the p-value is less than or equal to 0.05, the test rejects the normality hypothesis.
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Full Question :
Kurtosis is a measure of_____
a) how fat the tails of a distribution are
b) the downside risk of a distribution
c) the normality of a distribution
d) the dividend yield of the distribution
e) both how fate the tails of a distribution are and the normality of a distribution
