best practice in Sampling

In a keynote address at the Sampling 2008 conference in Perth, François-Bongarçon (2008) stated that the modern sampling theory (the Theory of Sampling – TOS) is enjoying its golden age, sixty years after its inception and after alternate periods of acceptance and
rejection by the industry. Pollard et al. (2009) explained that, from their experience in
industry, education, training, and professional development, the minerals industry regards
sampling as an important part of its operations, but often does not recognize the
differences between good and bad sampling practices.



 Poor understanding of sampling theory and how it should be applied, a corporate cost-saving culture, especially concerning technical issues that are not well understood by executive management, and a failure in the education of industry professionals to develop an understanding of the fundamentals and economic importance of good sampling practice, were listed as reasons  for this.

A growing understanding and appreciation of sampling theory and methods has led to a new era in which mining companies are in fact implementing new sampling procedures and
protocols. A comprehensive international sampling standard for the mining industry does not exist, but Minnitt (2007) suggested that standardization through the identification of structural problems and continuous improvement of sampling processes should be instituted at a national level in the interests of optimal development of the national patrimony.

Where necessary the principles of TOS are referred to in the body of the paper. The total sampling error (TSE) is the sum of all sampling variances contributed by the errors and bias-generating components in a sampling protocol. Contrary to the popular belief that the errors will ‘average out’, sampling errors are additive and not self-compensating. Gy (1979)
subdivided the errors involved in sampling into seven different classes without distinguishing
between accuracy, precision of measurement, or the natural variability of the material being sampled. Although eleven sources of sampling error have been identified not all the errors were named by Gy (1979); however, he did identify them in his writings.

The sampling errors that contribute to the nonrepresentativeness of samples were  described.

by I.C. Spangenberg*, and R.C.A. Minnitt

Full text in PDF:

Download