shapiro.test: Shapiro-Wilk Normality Test

shapiro.testR 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. \Sexpr[results=rd,stage=build]{tools:::Rd_expr_doi("10.2307/2347973")}.

Patrick Royston (1982). Algorithm AS 181: The W test for Normality. Applied Statistics, 31, 176–180. \Sexpr[results=rd,stage=build]{tools:::Rd_expr_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. \Sexpr[results=rd,stage=build]{tools:::Rd_expr_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))