Estimating error in measurements of mineral grain size distribution

By estimating how the error in the characteristic of interest reduces as particle sample size increases, the bootstrap resampling approach assists mineralogists to identify how many particles must be analysed to achieve the desired variance in the measured value. Examples from a copper porphyry ore are presented to illustrate the practical applications of this methodology in quantitative mineralogy programmes.