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Title: Statistical analysis of water-quality data affected by limits of detection

Thesis/Dissertation ·
OSTI ID:6503206

Many water-quality problems are related to substances present at concentrations too low to be measured precisely. Obtaining information from a monitoring system that produces many results near the fringes of analytic capabilities is not straightforward. This thesis discusses concerns one should have when statistically analyzing water-quality data from such a system. Two general approaches are discussed. The traditional approach is to regard all measurements as precise or imprecise. Precise results are simply numerical responses, for which statistical analysis may lead to valid and sound monitoring information. Imprecise results are reported as ND, or not detected, with criteria for reporting based on categories of measurement precision. Measurement error that leads to censoring is described. The impact of this error on the statistical characteristics of water-quality data is illustrated, using a model appropriate for analyte concentrations near the limit of detection. Loss of information due to censoring is demonstrated, and it is proposed that a numerical results be reported for all measurements. It is also suggested that an estimate of data precision accompany all results. This would permit the data user to censor at levels of uncertainty chosen by the user, rather than having information censored by the measurement process.

Research Organization:
Colorado State Univ., Fort Collins (USA)
OSTI ID:
6503206
Resource Relation:
Other Information: Thesis (Ph. D)
Country of Publication:
United States
Language:
English