A measure of "peakedness" of a probability distribution, defined as the fourth cumulant divided by the square of the variance of the probability distribution
(İstatistik) In probability theory and statistics, curtosis or kurtosis (from the Greek word kurtos, meaning bulging) is a measure of the "peakedness" of the probability distribution of a real-valued random variable. Higher kurtosis means more of the variance is due to infrequent extreme deviations, as opposed to frequent modestly-sized deviations
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 refered to as the volatility of volatility
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
Refers to the peakedness or flatness of a frequency distribution as compared with a normal distribution
A measure of the peakedness of a distribution calculated in several statlets This statistic is useful in determining how far your data departs from a normal distribution For the normal distribution, the theoretical kurtosis value equals 0 and the distribution is described as mesokurtic (Note: some authors define kurtosis such that a normal distribution has a value = 3 In STATLETS, the 3 has been subtracted away ) If the distribution has long tails (i e , an excess of data values near the mean and far from it) like the t-distribution, the statistic will be greater than 0 Such distributions are called "leptokurtic" Values of kurtosis less than 0 result from curves that have a flatter top than the normal distribution They are called "platykurtic" To judge whether data departs significantly from a normal distribution, a standardized kurtosis statistic can also be computed
A measure of the peakedness of a probability distribution For a random variable x with mean μ and standard deviation σ, kurtosis is the fourth central moment divided by the squared variance, E(x-μ)4/σ4 For a normal random variable, kurtosis is 3