Estimation of the mean and reproducibility of aggregate compositions basedon constituent mass data

Given a set of representative samples of aggregate source material (e.g. fr om a stockpile or production line), it is shown that if only percentaged da ta is reported, the mean composition of the percentaged data is best calcul ated using a robust estimate of the logratio mean. However, If raw mass dat a is also available (as will generally be the case), then it is best to fir st calculate the average of the constituent masses, and then to convert the se into a percentage. The difference between confidence; prediction and tol erance intervals is reviewed and it is shown that the repeatability of aggr egate samples and an effective long-term 'detection limit' for constituents :can be reliably estimated using duplicates of run-of-the-mill samples; an upper boundary can be:placed on the detection limit by application of, say, a two-sided {95%, 99%} tolerance interval. Numerical approximations are gi ven to enable a variety df normal two-sided tolerance factors to be compute d.