The Bayesian approach to sampling is characterized by a subjective approach to probability. One attractive feature of the Bayesian approach is the fact that a decision maker's 'degree of belief' in an unknown parameter changes with additional information. This characteristic provides an approach for the evaluation and update of sparse information.

An illustration using a sequential Bayesian algorithm is directed toward a common entomological problem: the estimation of pest abundance within a cotton field. The example shows how the use of more information influences the knowledge of an entomologist, and demonstrates how statements about the accuracy of that knowledge are readily available.