# shapiro.test

##### Shapiro-Wilk Normality Test

Performs the Shapiro-Wilk test of normality.

- Keywords
- htest

##### Usage

`shapiro.test(x)`

##### Arguments

- x
a numeric vector of data values. Missing values are allowed, but the number of non-missing values must be between 3 and 5000.

##### Value

A list with class `"htest"`

containing the following components:

the value of the Shapiro-Wilk statistic.

an approximate p-value for the test. This is
said in Royston (1995) to be adequate for `p.value < 0.1`

.

the character string `"Shapiro-Wilk normality test"`

.

a character string giving the name(s) of the data.

##### References

Patrick Royston (1982).
An extension of Shapiro and Wilk's \(W\) test for normality to large
samples.
*Applied Statistics*, **31**, 115--124.
10.2307/2347973.

Patrick Royston (1982).
Algorithm AS 181: The \(W\) test for Normality.
*Applied Statistics*, **31**, 176--180.
10.2307/2347986.

Patrick Royston (1995).
Remark AS R94: A remark on Algorithm AS 181: The \(W\) test for
normality.
*Applied Statistics*, **44**, 547--551.
10.2307/2986146.

##### See Also

`qqnorm`

for producing a normal quantile-quantile plot.

##### Examples

`library(stats)`

```
# NOT RUN {
shapiro.test(rnorm(100, mean = 5, sd = 3))
shapiro.test(runif(100, min = 2, max = 4))
# }
```

*Documentation reproduced from package stats, version 3.6.0, License: Part of R 3.6.0*