Shapiro-Wilk Normality Test
Performs the Shapiro-Wilk test of normality.
- a numeric vector of data values. Missing values are allowed, but the number of non-missing values must be between 3 and 5000.
- 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.
The algorithm used is a C translation of the Fortran code described in
Royston (1995) and found at
Patrick Royston (1982) An extension of Shapiro and Wilk's $W$ test for normality to large samples. Applied Statistics, 31, 115--124.
Patrick Royston (1982) Algorithm AS 181: The $W$ test for Normality. Applied Statistics, 31, 176--180.
Patrick Royston (1995) Remark AS R94: A remark on Algorithm AS 181: The $W$ test for normality. Applied Statistics, 44, 547--551.
qqnorm for producing a normal quantile-quantile plot.
shapiro.test(rnorm(100, mean = 5, sd = 3)) shapiro.test(runif(100, min = 2, max = 4))