Determining distribution of a set of ordered numbers I've always wondered this. Let's say someone gives you a spreadsheet with a large set of numbers, say 10,000, and says "What distribution does this set of numbers follow (Gaussian, exponential, Poisson, etc.)"? How do you go about determining the answer?
 A: I think you would formulate hypotheses about the distributions which you test on the data. The structure of data may give you hints on whether a discrete or a continuous distribution is at hand. A famous test is Kolmogorov Smirnov, which compares expected to observed cummulative distribution functions to test a hypothesized null distribution. See the wikipedia entry for this test for details:
http://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test
To test discrete distributions, a Chi² test is usually applied.
A: 
Let's say someone gives you a spreadsheet with a large set of numbers, say 10,000, and says "What distribution does this set of numbers follow (Gaussian, exponential, Poisson, etc.)"? How do you go about determining the answer?

If its real data, the actual answer is generally 'none of the above, nor anything else specific you can put a name to'.
You may be able to find one that is a reasonable description, but with a large enough sample size you could potentially reject every 'standard' distribution you try.
Note, particularly, that failure to reject some particular distributional guess with a hypothesis test doesn't imply that's the distribution you have -- nor does rejection imply that using the 'rejected' distribution as a model would yield results that aren't simultaneously reasonably accurate and quite informative.
With a sample size of 10000, I'd be saying "what do I need such an approximate model for? I have a sample of size ten thousand! I can estimate the distribution more accurately nonparametrically, whether by using the ECDF itself or by kernel methods or log-spline density estimation, or whatever"
You may find some useful insight in the discussion of these somewhat related questions here, here or here
