![]() Within each graph, the values on the right side of the distribution taper differently from the values on the left side. Thus, the judgement on the symmetry of a given distribution by using only its skewness is risky the distribution shape must be taken into account.Ĭonsider the two distributions in the figure just below. For example, a zero value in skewness 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. ![]() ![]() In cases where one tail is long but the other tail is fat, skewness does not obey a simple rule. The skewness value can be positive, zero, negative, or undefined.įor a unimodal distribution (a distribution with a single peak), 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 probability theory and statistics, skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean. ![]() These data are from experiments on wheat grass growth. For the planarity measure in graph theory, see Graph skewness.Įxample distribution with positive skewness. ![]()
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