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(v0.8.0.9036) complete documentation rewrite

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2019-11-28 22:32:17 +01:00
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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.
#'
#' 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.
#' @param x a vector of values, a \code{matrix} or a \code{data frame}
#' @param na.rm a logical value indicating whether \code{NA} values should be stripped before the computation proceeds.
#' @param x a vector of values, a [`matrix`] or a [`data.frame`]
#' @param na.rm a logical value indicating whether `NA` values should be stripped before the computation proceeds.
#' @exportMethod skewness
#' @seealso \code{\link{kurtosis}}
#' @seealso [kurtosis()]
#' @rdname skewness
#' @inheritSection AMR Read more on our website!
#' @export