högerskev

Högerskev is a term used in statistics (notably in Swedish-language texts) to describe a distribution that is not symmetric and has a longer tail on the right side. In English, the term corresponds to a right-skewed or positively skewed distribution.

Characteristics of a högerskev distribution include that the bulk of the data lie to the left of the distribution’s center, while a tail extends toward higher values. A common practical indicator is that the mean is greater than the median. Skewness is quantified by the skewness coefficient γ1, defined as the third standardized moment E[(X−μ)³]/σ³. For sample data, the estimate g1 = m3/s³ (with m3 the third central moment and s the sample standard deviation) is used. A positive γ1 indicates right skew; a negative value indicates left skew.

Common examples in real data sets include income distributions, certain insurance claims, and waiting times that are bounded below by zero but unbounded above. Skewness has implications for statistical analysis: many methods assume normality, and substantial skew can affect estimates and inference. Transformations such as logarithmic or square-root transforms can reduce skew, while alternative models that accommodate skewness—such as Gamma, lognormal, or certain count models—may be more appropriate. Nonparametric methods can also be robust to skew.

In reporting, researchers often accompany measures of central tendency with a skewness statistic and visual descriptions (histograms, Q-Q plots) to characterize the degree and direction of skew. See also left-skew and measures of distribution shape.