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In
this thread the question whether poker winrates are normally distributed came up (as normality is often assumed for calculating ROR).
I ran my
per hand winrates for 90k hands through every possible test for normality contained in the
R software package and each test rejected normality pretty badly.
Even by looking at a histogram of my winrates I can tell they cannot be normally distributed (and it's not even close).
I would like to hear some comments from you guys.
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What time period did each data point represent? If you plot win rates per hand, or per hour, or even per session, these will not be normal; however, if each data point represents a sufficiently long period of time, and there haven't been any major changes to the playing conditions, then you should see that the data begins to be well-approximated by a normal distribution, as guaranteed by the central limit theorem.