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**EmpSci** Oh, yes. I am familiar with the test procedure. The point where I am stuck is the theoretical probability evaluation, which is then subtracted from the empirical $\displaystyle p(x_i)$, squared and divided by theoretical probabilities. But, my difficulty is the evaluation of theoretical probabilities. I wanted to test for Poisson, and I am stuck on how to evaluate the Poisson probabilities.

All in all, I have $\displaystyle n$ observed probabilities (I do have the absolute frequencies, as well). The first few entries have the following values:

$\displaystyle p(x_1)=0.503, p(x_2)=0.25, p(x_3) = 0.0027, p(x_4) = 0.0024, ..., p(x_n)=1.03848E-05$. So, you can image, I suppose, the way this discrete distribution looks like. If not Poisson, then what other theoretical distribution would you recommend to consider?

Thanks!