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NOW <br />Appendix D, Section 1 <br />Description of Statistica-I Analyses <br />The statistical analyses used to determine if a discharge from the landfill is impacting <br />groundwater in the detection monitoring wells were selected in accordance with EPA <br />guidance (EPA, 1989) and State of California Regulations (23 CCR 2550). The procedure is <br />outlined in Figure D-1 and each step is discussed below. <br />Identification of Outliers <br />The test for outliers is to determine if there is statistical evidence that an observation <br />.pl. extreme and does not fit the distribution of the remainder of the data. Any <br />observations identified as outliers were assigned a value of in the Lab Flag field in the <br />database and were not used for statistical analysis. <br />To identify outliers, the statd as shown below, where X,, is the largest <br />observation, X is the mean of the observations, and S is the standard deviation. <br />The statistic T. is compared with a critical value for the sample size (EPA, 1989). The sample <br />was identified as an outlier if it met three conditions: (1) the statistic exceeds the critical <br />value, (2) the observation is at least four times greater than the mean, and (3) the <br />observation was at least four times greater than the next highest values. <br />Test for Normality <br />robust with respect to departures from many of the normal distribution assumptions (EPA, <br />1989). Extensive study of the distribution is not considered necessary unless a <br />L-ionparametric method of analysis.is selected. <br />The coefficient of variation was used to determine if the assumption of a normal <br />distribution was appropriate. The coefficient of variation is the standard deviation, 5, <br />divided by the mean of the observations, X. If the coefficient of variation exceeds one, there <br />is evidence that the data are not normal and the assumption of a normal distribution is not <br />appropriate for the data set. <br />If the data set appears to not be normally distributed, the residuals for the data set will be <br />checked for normality. If these are normal, the distribution of the data set will be assumed <br />normal and the parameteric test will be selected. If the residuals are not normally <br />distributed, the aata set will be transformed and checked for normality. If the transformed <br />data set is rionnal, the parametric procedure will be selected. If the transformed data set is <br />not normal, a nonparametric procedure will be used for the data set. <br />M-1 7MMIT3,11M."AM <br />