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Why does the Triad distinguish between “analytical quality” and “data quality”?

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Why does the Triad distinguish between “analytical quality” and “data quality”?

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Under the Triad approach, the data s ability to support the intended data use determines whether data quality is acceptable or unacceptable. This definition for “data quality” is consistent with recent EPA quality guidance. Since the data used to make project decisions are produced from environmental samples coming from heterogeneous matrices, the concept of “data quality” must include not just an assessment of analytical performance against data use, but also an expression of the sampling “performance” or sample representativeness. In other words, the Triad views data quality as an integration of both analytical quality and “sampling quality” (i.e., sample representativeness). If only the performance of the analytical method is under discussion, then the term “analytical quality” should be used to avoid confusion. In a Triad context, discussion of data quality must also include explicit discussion of sample representativeness in the context of the conceptual site model as it relates t

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