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(v1.3.0.9039) lifecycle updates, added excess kurtosis
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#'
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#' @description Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean.
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#'
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#' When negative: the left tail is longer; the mass of the distribution is concentrated on the right of the figure. When positive: the right tail is longer; the mass of the distribution is concentrated on the left of the figure.
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#' @inheritSection lifecycle Questioning lifecycle
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#' 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.
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#' @inheritSection lifecycle Stable lifecycle
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#' @param x a vector of values, a [`matrix`] or a [data.frame]
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#' @param na.rm a logical value indicating whether `NA` values should be stripped before the computation proceeds.
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#' @param na.rm a logical value indicating whether `NA` values should be stripped before the computation proceeds
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#' @seealso [kurtosis()]
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#' @rdname skewness
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#' @inheritSection AMR Read more on our website!
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