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))
# }