A Bayesian method for computing sample size and cost requirements for stratified random sampling of pond water

Academic Article

Abstract

  • Estimating average environmental pollution concentrations and its variance is a fairly straight forward task in stratified random sampling. A more challenging concept is the introduction of the cost factor into this environmental model. Traditional statistical techniques have incorporated costs from sampling within a stratum as well as stratum weights to determine the stratum size and overall required sample size. Information in the form of informative prior distributions to determine a more coherent variance in the system yield a more precise Bayesian approach to the sample size and cost calculations. This approach results in a more efficient sampling strategy in terms of cost when considering a pre-specified margin of error for the sampling mean as well as the more complicated situation of correlation among the stratum samples. © 2005 Elsevier Ltd. All rights reserved.
  • Published In

    Digital Object Identifier (doi)

    Author List

  • Bartolucci AA; Bartolucci AD; Bae S; Singh KP
  • Start Page

  • 1319
  • End Page

  • 1323
  • Volume

  • 21
  • Issue

  • 9