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50 lines
1.1 KiB
Markdown
50 lines
1.1 KiB
Markdown
# Skewness of the Sample
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Skewness is a measure of the asymmetry of the probability distribution
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of a real-valued random variable about its mean.
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When negative ('left-skewed'): the left tail is longer; the mass of the
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distribution is concentrated on the right of a histogram. When positive
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('right-skewed'): the right tail is longer; the mass of the distribution
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is concentrated on the left of a histogram. A normal distribution has a
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skewness of 0.
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## Usage
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``` r
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skewness(x, na.rm = FALSE)
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# Default S3 method
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skewness(x, na.rm = FALSE)
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# S3 method for class 'matrix'
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skewness(x, na.rm = FALSE)
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# S3 method for class 'data.frame'
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skewness(x, na.rm = FALSE)
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```
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## Arguments
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- x:
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A vector of values, a [matrix](https://rdrr.io/r/base/matrix.html) or
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a [data.frame](https://rdrr.io/r/base/data.frame.html).
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- na.rm:
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A [logical](https://rdrr.io/r/base/logical.html) value indicating
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whether `NA` values should be stripped before the computation
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proceeds.
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## See also
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[`kurtosis()`](https://amr-for-r.org/reference/kurtosis.md)
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## Examples
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``` r
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skewness(runif(1000))
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#> [1] -0.01429035
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```
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