Soil Sampling for Enviromental Contaminants (IAEA TECDOC

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For example, a desired measurement quality objective to have data with variability not exceeding plus or minus 10% at a 95% confidence level represents the case where the value of 450 to 550 mg kg-1 would be obtained in 95 out of a hundred times that a sample containing 500 mg kg-1 of the target analyte was analysed. Circumstances that do not permit sufficient samples to be analysed may result in either a lesser confidence level (for example, plus or minus 10% at a 60% confidence level) or a greater variability (for example plus or minus 25% at a 95% confidence level).

For the analytical laboratory, the analytical precision specified needs to be less than 4% (at 95 % confidence level) at concentration level ten times above the detection limit (specified as 20 mg kg-1 Pb). If this criterion is not met, then the lab will reanalyse the samples and QC materials, by an alternative analytical method if appropriate. Enviro-Calc may be used as an initial estimate of the numbers of samples that need to be analysed to generate data with no more than 20% relative standard deviation at 95% confidence and with a tolerable error not exceeding 10%, in order to have the already specified target uncertainty (at 95% confidence) at concentrations more than ten times the detection limit (20 mg kg-1).

G. linear) can be developed on many calculators or computer databases; however, a statistician should be consulted to check the accuracy of more complex models. Evaluation of the accuracy of a model in part relies on statistical correlation. Statistical correlation involves computing an index called the correlation coefficient I that indicates the degree and nature of the relationship between two or more sets of values. 0 (a perfect direct, or positive, relationship). The square of the correlation coefficient, called the coefficient of determination, or simply R2, is an estimate of the proportion of variance (standard deviation squared) in one variable (the dependent variable) that can be accounted for by the independent variables.

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