Hiya eastbay,
There are formulae for confidence intervals (statistical margins of error) of independent data. For independent data -- e.g.: polling data -- with a very large population, you need a sample size of about 384 to get the confidence interval down to +/- 5%. (See:
http://www.surveysystem.com/sscalc.htm )
However, poker results are not independent data. In poker, your opponents get to know you. You get to know them. Your play may improve. A run of bad beats -- or "bad" wins -- may temporarily put you off your best game. And so on.
Poker results are quasi-Markhov Chain data. That is, prior events affect (but do not determine) future results. (See
http://www.indiainfoline.com/bisc/jama/jmmm.html ) You need a much larger sample set in order to get the same confidence interval for quasi-Markhov data, typically 3-5x the sample size needed for independent data, depending on the extent of the Markhov effect.
In short, you need about 1200 SNGs to get the margin of error to within 5%.
If you have 300 SNGS at buy-in A and an ROI of 40%, your confidence interval is around 10%. That means you can be 95% sure that your long-term ROI at that buy-in will be between 30% and 50% ... but any number in that range is as likely as any other. You don't have enough data to narrow it farther than that. If you have 300 SNGs at buy-in B and an ROI of 30%, your long-term ROI there could be anywhere from 20%-40%.
So you can't draw any meaningful conclusions about them from only 300 samples each, despite the seemingly obvious greater success at A, because the ranges overlap so much that the difference may be merely a statistical anomaly (you got luckier at A than at B, or were tilting a bit for some of the Bs, or etc.).
Cris