Abstract
AbstractThis is a study of Bayesian data worth analysis in environmental clean‐up applications. Its focus is on calculating the worth of simultaneously taking several (soil) samples in a small homogeneous area and on finding the optimal number of samples to take, by relating the reduction in risk cost from sampling, that is, data worth, to the cost of the samples. Even though the cost of one sample may be higher than the risk cost reduction it provides, this study shows that several samples may be cost‐efficient. This is mainly due to two factors: one is that the unit sample cost often decreases as the number of samples increase; another, more important, factor is that the data worth of several samples typically is higher than the worth of fewer samples. Copyright © 2006 John Wiley & Sons, Ltd.
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