The use of simulations to determine sampling errors

Abstract

The present paper provides a comprehensive approach to the use of simulations to determine sampling errors for three broad classifications of analyte characteristics: low concentrations of analyte mostly occluded within gangue grains, low concentrations of analyte occurring mainly as liberated grains and higher analyte concentrations. Poisson distributions are used for simulations for the first two of these classifications and a binomial distribution is used for the third. The methodology requires that samples are screened and each size fraction is weighed and assayed. Fortran computer codes and accompanying data sets are provided for each of the three classifications in the accompanying Appendixes. Outputs from the simulations are compared with the error variances generated by Gy's sampling formula.