My question is similar to this post (KS test for Uniformity). KS p-valuse changes when samples are in different position, even if they have the same intervals. For example:
ks.test(c(1,2,3),"punif",1,100)
D = 0.9798, p-value = 1.649e-05
ks.test(c(51,52,53),"punif",1,100)
D = 0.50505, p-value = 0.3217
How to explain why these two tests give different result?
My sample sizes are relatively small (2~30) and I know it maybe too hard to make any conclusion, but still, is there a way to test see if my samples distribution is random (uniform) or cluster in a certain region.
Thank you.
