I created a sample with 10000 normally distributed numbers. Subsequently, I used the Kolmogorov-Smirnov test to check if they are indeed normally distributed, and it turned out that they are not. How is this possible?
Below is my code.
data <- rnorm(n=10000, 5, 2) ks.test(data, "pnorm")
And this is the answer:
Exact one-sample Kolmogorov-Smirnov test
data: data D = 1, p-value < 2.2e-16 alternative hypothesis: two-sided