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ksnormal is a convenience function around ks.test, testing against Normal distribution. If less than 2 values are provided, NA is returned.
ksnormal
ksnormal(x, lillie = TRUE)
p.value from ks.test.
Vector of data to test.
Logical, should the Lilliefors test be used? Defaults to TRUE
# original ks.test: ks.test( x = mtcars$wt, pnorm, mean = mean(mtcars$wt, na.rm = TRUE), sd = sd(mtcars$wt, na.rm = TRUE) ) # wrapped version: ksnormal(x = mtcars$wt, lillie=FALSE)
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