The recent revisions of Federal Standard 209 regarding clean-rooms include two statistical tests for the concentration data obtained from sampling airborne particles: a) that none of the location averages exceeds the Class Limit (CL) and b) that there be 95 percent confidence that the true mean of the location averages does not exceed the CL, based on the data making up the grand mean of averages. For sampling from a constant and uniform concentration (Poisson data) or from a concentration giving data that are normally distributed, we show the statistical implications of choosing a certain level of confidence that no location average exceed CL. Similarly, we show the statistical implications of the 95 percent confidence requirement on the grand mean. For any situation where each location has approximately the same standard deviation in its readings, the Poisson and normal distributions included, if one has 95 percent confidence that none of the locations exceeds the CL, the requirement for the grand mean is also likely to be met if five or more locations are sampled. Simulation methods can assist prediction, and several methods are summarized. The likelihood of meeting the standard can usually be improved by: reducing the average concentration and the variability of the concentration (through design and good practices), increasing the number of samples per location and the volume sampled for each, and keeping the number of locations sampled to the minimum allowed.

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