This sub-page of the Data Analysis page displays results of specific tests on the data values from the Data Entry Sub-page.
This page contains the following controls / displays:
Normal Distribution Test |
VSP conducts a Shapiro-Wilk normality test if there are fewer than 50 selected data values; otherwise a Lilliefors normality test is conducted. |
Upper Confidence Limit on Mean |
VSP uses two methods for computing the UCL on the mean: one assumes the data are normally distributed ( Parametric UCL ), the other does not ( Nonparametric UCL ). |
Statistical Test for Comparing the Mean to a Threshold |
VSP conducts one of two statistical tests to compare the mean against a threshold. If the data appears to be normally distributed, the One-Sample t-Test is conducted; otherwise the MARSSIM Sign Test is conducted. |
Conover, W.J. 1999. Practical Nonparametric Statistics, 3rd edition, Wiley, NY.
Gilbert, R.O. 1987. Statistical Methods for Environmental Pollution Monitoring, Wiley, NY.
ProUCL. 2004. ProUCL Version 3.0 User Guide April 2004. Available for download from http://www.epa.gov/nerlesd1/tsc/tsc.htm.
VSP uses two methods to compute the UCL or the LCL of the mean: one method assumes the distribution of the sample mean is approximated by a t distribution, and the other makes no parametric assumptions regarding the distribution of the sample mean. If the null hypothesis is that the true mean is ≥ action level (site is dirty), then the UCL is reported. Otherwise, if the null hypothesis is that the true mean ≤ action level (site is clean), the LCL is reported.
VSP conducts a statistical test to compare the mean against a threshold using an approximate one-sample t-test for non-detect data.
Gilbert, R.O. 1987. Statistical Methods for Environmental Pollution Monitoring . John Wiley & Sons, Inc. New York, NY.
Singh, A., R. Maichle, and S.E. Lee. 2006. On the Computation of a 95% Upper Confidence Limit of the Unknown Population Mean Based Upon Data Sets with Below Detection Limit Observations . Prepared for the EPA. Report # EPA/600/R-06/022. pp 30-32.