Statistical evaluation of cleanup: How should it be done?

This paper discusses statistical issues that must be addressed when conducting statistical tests for the purpose of evaluating if a site has been remediated to guideline values or standards. The importance of using the Data Quality Objectives (DQO) process to plan and design the sampling plan is emphasized. Other topics discussed are: (1) accounting for the uncertainty of cleanup standards when conducting statistical tests, (2) determining the number of samples and measurements needed to attain specified DQOs, (3) considering whether the appropriate testing philosophy in a given situation is ''guilty until proven innocent'' or ''innocent until proven guilty'' when selecting a statistical test for evaluating the attainment of standards, (4) conducting tests using data sets that contain measurements that have been reported by the laboratory as less than the minimum detectable activity, and (5) selecting statistical tests that are appropriate for risk-based or background-based standards. A recent draft report by Berger that provides guidance on sampling plans and data analyses for final status surveys at US Nuclear Regulatory Commission licensed facilities serves as a focal point for discussion