I have some discrete times of events and I would like to do a test to see if they are likely to have come from a homogeneous Poisson process.
From this pdf, I see:
REMARK 6.3 ( TESTING POISSON ) The above theorem may also be used to test the hypothesis that a given counting process is a Poisson process. This may be done by observing the process for a fixed time $t$. If in this time period we observed n occurrences and if the process is Poisson, then the unordered occurrence times would be independently and uniformly distributed on $(0, t]$. Hence, we may test if the process is Poisson by testing the hypothesis that the n occurrence times come from a uniform $(0, t]$ population. This may be done by standard statistical procedures such as the Kolmogorov-Smirov test.
However I don't quite understand what to do in practice. Say my times are
[1, 7, 18, 22, 41, 43, 66, 73, 86, 92]
and the time interval I chose was from $1$ to $100$. How exactly do I do the Kolmogorov-Smirov test in this example?