This sounds to me to be an issue of the 'statistical power'. From
wikipedia:
Quote:
Statistical power may depend on a number of factors. Some of these factors may be particular to a specific testing situation, but at a minimum, power nearly always depends on the following three factors:
the statistical significance criterion used in the test
the magnitude of the effect of interest in the population
the sample size used to detect the effect
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there are a number of websites that can help with these calculations if you input the data. I'm not an expert in this area, but you may need some sample data as a starting point to estimate the effect size (eg. penny vs. dime), and your statistical significance criteria (alpha) is the probability that the effect is not due to chance (typically 5% or alpha=0.05, but may be smalled based on the stated problem)
/geek
