Calculate skew and kurtosis — skew

Calculate skew and kurtosis, standard errors for both, and the estimates divided by two times the standard error. If this latter quantity exceeds an absolute value of 1, the skew/kurtosis is significant. With very large sample sizes, significant skew/kurtosis is common.

Usage

skew_kurtosis(x, verbose = FALSE, se = FALSE, ...)

Arguments

x: An object for which a method exists.
verbose: Logical. Whether or not to print messages to the console, Default: FALSE
se: Whether or not to return the standard errors, Default: FALSE
...: Additional arguments to pass to and from functions.

Value

A matrix of skew and kurtosis statistics for x.

Examples

skew_kurtosis(datasets::anscombe)
#>           skew   skew_2se       kurt   kurt_2se
#> x1  0.00000000  0.0000000 -1.5289256 -0.5975093
#> x2  0.00000000  0.0000000 -1.5289256 -0.5975093
#> x3  0.00000000  0.0000000 -1.5289256 -0.5975093
#> x4  2.46691100  1.8669273  4.5206612  1.7666896
#> y1 -0.04837355 -0.0366085 -1.1991228 -0.4686212
#> y2 -0.97869294 -0.7406626 -0.5143191 -0.2009976
#> y3  1.38012040  1.0444578  1.2400439  0.4846133
#> y4  1.12077386  0.8481876  0.6287512  0.2457181