Moment (mathematics) | Statistical deviation and dispersion

Skewness

In probability theory and statistics, skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean. The skewness value can be positive, zero, negative, or undefined. For a unimodal distribution, negative skew commonly indicates that the tail is on the left side of the distribution, and positive skew indicates that the tail is on the right. In cases where one tail is long but the other tail is fat, skewness does not obey a simple rule. For example, a zero value means that the tails on both sides of the mean balance out overall; this is the case for a symmetric distribution, but can also be true for an asymmetric distribution where one tail is long and thin, and the other is short but fat. (Wikipedia).

Skewness
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SPSS | Mode (statistics) | Moment (mathematics) | Absolute value | Shape parameter | Skewness | Skew normal distribution | Mean | Statistics | Central moment | Normality test | Cumulative distribution function | Sample mean | Statistical dispersion | Exponential distribution | Quantile function | Outlier | Confidence interval | Heavy-tailed distribution | Method of moments (statistics) | Median | L-moment | Bias of an estimator | Skewness risk | Standardized moment | D'Agostino's K-squared test | Variance | Half-normal distribution | Histogram | Nonparametric skew | Average absolute deviation | Coskewness | Long tail | Real number | Value at risk | Probability distribution | Normal distribution | Standard deviation | Random variable | Expected value | Medcouple | Consistent estimator | Probability theory | Kurtosis | Multimodal distribution | Symmetric probability distribution | SAS (software) | Cumulant