Part 1: Understanding the components of the fundamental sampling error: a key to good sampling practice - Synopsis

The variety and sources of sampling errors have been studied since the late 1800s, but the pioneering work of Pierre Gy in the 1950s provided insights into sampling as an error generating process. Total sampling variance is a measure of the total sampling error, but disaggregating the variance into its component parts is problematical. Ten sources of error and error generating processes have been identified, some of which can be eliminated through rigorous application of the principle of correct sampling. Others can only be minimized but never eliminated. Three principal questions relating to the appropriate mass of a sample, the fragment size of the sample and the size of the associated error are addressed. These questions relate principally to the Fundamental Error (FE), the only error that can be estimated before the sampling event. Aspects of constitutional and distributional heterogeneity are examined, as are the essential components of Gy?s formula including the shape factor (?), the granulometric factor (g), the mineralogical composition factor (c), and the liberation factor, l. Applications of Gy?s equation to the problems of sampling in the minerals industry are explained using real-life examples. The approach to sampling taken by Pierre Gy provides an excellent inferential relationship between the mass of material to be sampled, the size of the fragments being sampled, and the relative variance of the sampling error. It also provides solutions for three of the main problems associated with the Theory of Sampling.