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A measure of the asymmetry of the probability distribution of a real-valued random variable; is the third standardized moment, defined as \scriptstyle\gamma_1 = \frac{\mu_3}{\sigma^3}, \! where \mu_3 is the third moment about the mean and \sigma is the standard deviation

(In probability theory and statistics) A measure of the asymmetry of the probability distribution of a real-valued random variable about its mean

A statistic which measures the lack of symmetry in a distribution A plot of a skewed distribution would show a long tail to either the left or the right Distributions with a longer upper tail are said to be positively (right) skewed, while those with a longer lower tail are negatively (left) skewed The skewness of data is usually measured through a coefficient of skewness which is zero for symmetric distributions such as the normal or uniform distribution, is greater than zero for positively skewed data, and is less than zero for negatively skewed distributions To judge whether data departs significantly from a normal distribution, a standardized skewness statistic can also be computed Skewness is calculated in the One Variable Analysis statlet

The property of being skew

skewness of the histogram

Negative skewness means there is a substantial probability of a big negative return Positive skewness means that there is a greater than normal probability of a big positive return

A measure of the asymmetry of the probability distribution of a real-valued random variable; is the third standardized moment, defined as scriptstylegamma_1 = frac{mu_3}{sigma^3}, ! where mu_3 is the third moment about the mean and sigma is the standard deviation

A measure of the symmetry of a probability distribution For a random variable x with mean μ and standard deviation σ, skewness is the third central moment divided by the cubed standard deviation, E(x-μ)3/σ3 For a normal variable, skewness is 0 (See also Volatility skew )

This is a reference to the shape of a histogram of tree lengths that can be produced after searching through treespace Studies of random datasets have shown that the distribution of tree lengths is approximately normal, whereas in general datasets with a reasonable amount of signal have few shortest trees and few trees nearly as short There is a G-statistic for the skewness of a histrogram

obliqueness, quality of being oblique

an oblique or slanting asymmetry

Skewness is an asymmetrical frequency distribution in which the values are concentrated on one side of the central tendency and trail out on the other side If the trail is to the right or positive end of the scale, the distribution is said to be positively skewed If the distribution trails off to the left or negative side of the scale, it is said to be negatively skewed

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