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® Nonparametric Tolerance Limit <br /> When the background data set contains greater than 50 percent but less than 100 percent <br /> nondetect values and/or its distribution is not normal (or transformed normal), Sanitas applies the <br /> nonparametric tolerance limit method. However,this method requires a large number of samples <br /> to achieve a false positive rate of 1 percent or less, which is required by CCR Title 27 guidelines. <br /> Thus, when the alpha level was higher than 1 percent, the concentration limit was not established <br /> and data was compared to established limits in the Waste Discharge Requirements. <br /> Nonstatistical Approach <br /> When the background data set contains 100 percent nondetect values, Sanitas applies the <br /> nonstatistical approach. This approach takes into consideration that if historically a constituent <br /> has not been detected, any detection of that constituent would be considered an exceedence. <br /> Thus, in these situations (100 percent nondetected values), the tolerance limit is set at"detect' <br /> meaning that if a value is detected above its method detection limit,this value is an exceedance <br /> of the concentration limit. <br /> Intrawell Rank Sum <br /> When Intrawell Tolerance Limit analysis is unable to normalize the data and thus a <br /> nonparametric analysis is performed,the false positive rate becomes greater than five percent. <br /> When this happens,the data is compared to the concentration limit listed in the WDRs, if any. In <br /> ® addition, an Intrawell Rank Sum analysis is performed. This is a nonparametric procedure where <br /> the sums of ranked data sets are compared. Subsequent sample data are compared with sampling <br /> data from the initial monitoring period of the same well. It is assumed that during the initial <br /> monitoring period the well has shown no evidence of contamination nor an increasing trend. <br /> This test procedure is used to evaluate whether the historical (background data) and the <br /> compliance data have the same median constituent concentration. <br /> Trend Analysis <br /> Sen's Slope measures the change in constituent concentrations per unit time. Sen's method is <br /> not greatly affected by outliers, and the slope can be computed when data are missing. Sen's <br /> estimator is closely related to the Mann-Kendall test, which is a nonparametric rank correlation <br /> test for trend. The test uses only the relative magnitudes of the data rather than their actual <br /> values; therefore, missing values are allowed. Sen's Slope and the Mann-Kendall tests are <br /> described in"Statistical Methods for Environmental Pollution Monitoring,"Richard O. Gilbert, <br /> Van Nostrand Reinhold,New York, 1987. The Mann-Kendall test is recommended in"An <br /> Evaluation of Trend Detection Techniques for Use in Water Quality Monitoring Programs,"Jim <br /> Loftis, et al., (USEPA), 1989. <br /> Only data detected at least four times above its PQL are evaluated. Trace values used are the <br /> estimated values from the certified analytical reports. A trend analysis was conducted only on <br /> data collected from the point data was detected above the PQL. For the Corral Hollow Sanitary <br /> ® Landfill,the null hypothesis is"no statistically significant trend in constituent concentrations." <br /> Corral Hollow Landfill D-6 Department of Public Works/Solid Waste <br /> 4th Quarter and Annual 2012 Groundwater Monitoring County of San Joaquin—January 15,2013 <br />