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Associated Qualifiers <br /> Reliable results are discussed in terms of accuracy, precision, representativeness, <br /> comparability and completeness. The qualifiers associated with this review are as <br /> follows: <br /> Accuracy -Accuracy is measured by determining the percent recoveries of the laboratory <br /> control sample, the matrix and the matrix spike duplicate and for organic analyses the <br /> surrogate. The following equation is used to calculate the accuracy in terms of% <br /> recovery. <br /> %R= [(SSR-SR)xI00]/SA <br /> SSR= Spiked sample result <br /> SR= Sample result <br /> SA= Spike added <br /> The laboratory established the range of percent recoveries as determined by the <br /> appropriate methods. If the percent recoveries of the matrix spike or the matrix spike <br /> duplicate fall outside the control limit, this may be due to a matrix effect. This may not <br /> be a factor for establishing that the associated results are questionable. However, if the <br /> percent recovery for the laboratory control sample is outside the control limit the <br /> associated result is questionable and is determined an estimate. <br /> Precision - The precision of analysis is determined by spiking the matrix sample and a <br /> duplicate sample with a known amount of analyte. The precision can be measured as the <br /> relative percent difference (RPD) as can be calculated as follows: <br /> %RPD = [(X1-X2)/ (XI+X2)/2)] x 100 <br /> X I is the Ist duplicate value <br /> X2 is the 2nd duplicate value <br /> The % RPD is determined by the MS and MSD. <br /> Representativeness - Representativeness expresses the degree to which sample data <br /> accurately and precisely represent the comparison of analytical results from repeated <br /> analysis from the same sampling point over a period of time. <br /> Completeness - Completeness of data is defined as the amount of valid data obtained <br /> versus the expected amount of valid data(10 samples had valid data in a data package. 5 <br /> samples were either rejected or estimated). Percent completeness is calculated as <br /> follows: <br /> [(10 valid sample results)/(15 samples expected valid)] X 100 = 66% complete <br /> The completeness objective for most projects is 90% <br /> 2 <br />