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Fyrosfreddy
1. The sample size isn't that small: 542 Jool Crafts + 157 LA Crafts = 699

I beg to disagree, FF. You did, indeed, include *all* your results in the count. This is good experimental practice. However, my statement was:
Bitttymacod
When testing the overall rate of a process affected by an RNG you really need three or four thousand trials before you put a decimal on the percentage.
(emphasis added)

The reason for this is based in the mathematics of measurements of events controlled by chance.

When judging the margin of error of a measurement of events generated by random counts, the standard uncertainty is equal to the square root of the number of counts and the 95% expectation level is +/- 3 s.u. The square root of 53 is (approximately) 7. That means that a measured value of 53 could be the measurement of an expectation value (what the theory says) of any number between 74 and 32 at a 95% confidence level. This includes the number 70, which is the expectation value of a 10% success rate for the process in question, and also includes 35 which is the expectation value of a 5% success rate. In other words your current measurement (while *suggestive* of a lower rate than 10%) is not based on enough trials to reliably tell the difference between a 10% rate and a 5% rate.

If you have done 4000 trials the 10% success expectation value is 400 with an s.u. of 20. The expectation value of the 7% success is 280 with an s.u. of 17. A measurement of 370 (9.2%)would be consistent with the former, but not the latter. A measurement of 314 (7.8%) would be consistent with the latter and not the former. Your counting statistics would then be good enough to tell the difference between 10% and 7%. However, even a measurement of 280 cannot yet tell the difference between an 8% and a 6% expectation value, nor would a value of 400 be able to reliably say that the expectation value was not 9% or 11%.

In order to get good (trustable) statistics for a measurement like this, you need a *lot* of trials. The lower the expectation rate of "success" the more trials you need.

All that having been said, a simple answer from the devs as to whether or not they have mucked with the probabilities would save us both a *lot* of time.

-- With respect -- Bittty (who had to deal with this problem at his job all the time).

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