stats (version 3.6.2)

shapiro.test: 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.

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

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

Run the code above in your browser using DataCamp Workspace