R: Shapiro-Wilk Normality Test

shapiro.test {stats} | R Documentation

## Shapiro-Wilk Normality Test

### Description

Performs the Shapiro-Wilk test of normality.

### 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:

`statistic` | the value of the Shapiro-Wilk statistic.
`p.value` | an approximate p-value for the test. This is said in Royston (1995) to be adequate for `p.value < 0.1`.
`method` | the character string `"Shapiro-Wilk normality test"`.
`data.name` | a character string giving the name(s) of the data.

### Source

The algorithm used is a C translation of the Fortran code described in Royston (1995). The calculation of the p value is exact for n = 3, otherwise approximations are used, separately for 4 ≤ n ≤ 11 and n ≥ 12.

### References

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

Patrick Royston (1982). Algorithm AS 181: The W test for Normality. Applied Statistics, 31, 176–180. doi: 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. doi: 10.2307/2986146.

### See Also

`qqnorm` for producing a normal quantile-quantile plot.

### Examples

    shapiro.test(rnorm(100, mean = 5, sd = 3))
    shapiro.test(runif(100, min = 2, max = 4))

[Package stats version 4.0.5 Index]