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Skewness of the Sample

Source: R/skewness.R
skewness.Rd

Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean.

When negative ('left-skewed'): the left tail is longer; the mass of the distribution is concentrated on the right of a histogram. When positive ('right-skewed'): the right tail is longer; the mass of the distribution is concentrated on the left of a histogram. A normal distribution has a skewness of 0.

Usage

skewness(x, na.rm = FALSE)

# S3 method for default
skewness(x, na.rm = FALSE)

# S3 method for matrix
skewness(x, na.rm = FALSE)

# S3 method for data.frame
skewness(x, na.rm = FALSE)

Arguments

x

a vector of values, a matrix or a data.frame

na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds

See also

kurtosis()

Examples

skewness(runif(1000))
#> [1] -0.03310027