This follows on from the previous question on differences between K-S manual test and K-S test with R.
My frequency sample was
Then the observed sample is
The expected sample is then
I hope you agree.
First, I use
ks.test, like another time:
ks.test(obs,exp) data: oss and att D = 0.4667, p-value = 0.07626
Then, I use the ks.test the other way:
The expected distribution can be the uniform. Do you agree?
ks.test(obs, "punif", 0,5) data: obs D = 0.6667, p-value = 3.239e-06
- Why do the two approaches give different results?