An analysis of the viability of ranked set sample methodologies based on the evaluation of Dyess AFB B-47 crash site radiological contamination survey data and theoretical modifications Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/0k225d59p

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  • Since Ranked Set Sampling (RSS) was proposed in 1952 by G.A. McIntyre, it has been the subject of many statistical investigations and a large number of field studies. Throughout these studies RSS has been proven to provide a better estimate of population the mean and variance than Simple Random Sampling (SRS). Generally stated, RSS is the application of a screening methodology to evaluate a larger quantity of locations and then selectively choose those locations that would have more expensive and accurate sample analysis measurements. Specifically, its most commonly cited advantage is a more precise estimate of the mean if the same number of measurements is obtained using SRS. The most recent and publicly available methods for RSS use in radiological contamination evaluations have been accomplished by Oak Ridge Associated Universities (ORAU). Overall, RSS does not have extensive published literature regarding use or application for solely radiation clean up surveys. However, many literature articles and the US Environmental Protection Agency's guidance manuals on RSS often use a radiation contamination scenario as example where RSS could be useful compared to SRS. The focus of this study is to utilize the Dyess Air Force Base B-47 crash site data as a framework for a retrospective analysis of RSS. Specifically, the considerations to be assessed are the following: 1) What are the effects on the precision and accuracy of RSS mean estimate compared to that of SRS, when considering the Dyess survey and theoretical modifications, 2) Is there an optimal means to apply RSS for this survey or other radiological contamination surveys and lastly, 3) Given the procedures for RSS, could the field survey techniques used in this survey be utilized as a screening tool for determining what soil samples should be used in this survey, or future surveys of a similar nature?
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  • description.provenance : Approved for entry into archive by Julie Kurtz(julie.kurtz@oregonstate.edu) on 2015-04-15T15:47:15Z (GMT) No. of bitstreams: 2 license_rdf: 1379 bytes, checksum: da3654ba11642cda39be2b66af335aae (MD5) MillerVivienJ2015.pdf: 1796281 bytes, checksum: 8e6ef05ff53c34f3c37e3dd7523dbc21 (MD5)
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