# How to verify assumptions of a normal distribution? [duplicate]

I'm working with the iris data.I made a density plot And a qq plot For sepal Length.It looks Approximately normal With the left skew And a flat peak

The points In the qq Plot Stay within The confidence bands With the exception of smaller values

Would you classify This variable As normally distributed?

Are there more Empirical tests For validating normality?

The dataIs availableWith this code chunk

dni3 <- dimnames(iris3)
ii <- data.frame(matrix(aperm(iris3, c(1,3,2)), ncol = 4,
dimnames = list(NULL, sub(" L.",".Length",
sub(" W.",".Width", dni3[[2]])))),
Species = gl(3, 50, labels = sub("S", "s", sub("V", "v", dni3[[3]]))))
all.equal(ii, iris) # TRUE


These are the commands for the plots

library('car')
plot(density(Sepal.Length))
qqPlot(Sepal.Length)


And these are the plots