Censored environmental data presents unique challenges from "summary" of Statistics for Censored Environmental Data Using Minitab and R by Dennis R. Helsel
Censored environmental data, where some of the values are below detection or above quantification limits, poses unique challenges for statistical analysis. These challenges stem from the fact that censored data violate the usual assumption of a complete and accurate set of observations. In environmental studies, censored data are common due to measurement limitations, regulatory requirements, or other practical constraints. The presence of censored data can lead to biased estimates and incorrect inferences if not properly addressed. Ignoring censored values or treating them as exact measurements can result in misleading conclusions about the true distribution of the data. Therefore, it is essential to use appropriate statistical methods that account for the censored ...
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