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

## Examples

```
skewness(runif(1000))
#> [1] 0.02181457
```