Computes (standardized) interquartile range of the `x`

values.

```
IQrange(x, na.rm = FALSE, type = 7)
sIQR(x, na.rm = FALSE, type = 7, constant = 2*qnorm(0.75))
```

x

a numeric vector.

na.rm

logical. Should missing values be removed?

type

an integer between 1 and 9 selecting one of nine quantile
algorithms; for more details see `quantile`

.

constant

standardizing contant; see details below.

This function `IQrange`

computes quartiles as
`IQR(x) = quantile(x,3/4) - quantile(x,1/4)`

.
The function is identical to function `IQR`

. It was added
before the `type`

argument was introduced to function `IQR`

in 2010 (r53643, r53644).

For normally \(N(m,1)\) distributed \(X\), the expected value of
`IQR(X)`

is `2*qnorm(3/4) = 1.3490`

, i.e., for a normal-consistent
estimate of the standard deviation, use `IQR(x) / 1.349`

. This is implemented
in function `sIQR`

(standardized IQR).

Tukey, J. W. (1977). *Exploratory Data Analysis.* Reading: Addison-Wesley.

# NOT RUN { IQrange(rivers) ## identical to IQR(rivers) ## other quantile algorithms IQrange(rivers, type = 4) IQrange(rivers, type = 5) ## standardized IQR sIQR(rivers) ## right-skewed data distribution sd(rivers) mad(rivers) ## for normal data x <- rnorm(100) sd(x) sIQR(x) mad(x) # }