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AWWA WQTC69417
- Getting Better Microbial Data: Strategies to Quantify and Reduce Uncertainty
- Conference Proceeding by American Water Works Association, 11/01/2008
- Publisher: AWWA
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The objectives of this study were to:enable quantitative estimation of variability in microbialdata as a technique for evaluating experimental design; and,provide a tool that enables comparison of sampling andmethodological errors so that analysts can focus efforts onreducing the dominant error. Variability in enumeration methods:five categories of sampling and methodological errors have beenidentified in probabilistic models that enable more rigorousstatistical analysis of microbial enumeration data, including the following:Representative sampling-variability due to spatial or temporalheterogeneity of the source (samples arenot replicates);Random sampling error-variability in the number of microbialparticles captured in replicate samples ofthe same volume;Random analytical error-variability in the number of microbialparticles observed due to method losses;Non-constant analytical recovery-variability in the recovery efficiency ofthe method between equivalentlyprocessed samples; and,Counting error-variability in the number of observationsbetween repeat counts of the same sampleby the same or different analysts. Includes 4 references, figures.
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