Supporting Dataset (Tables S1-S7, Figure S1) for "Heavy-mineral grain counting: Counting techniques, error estimation, and the number of grains to be counted"

This Dataset comprises Tables S1-S7 for the article "Heavy-mineral grain counting: Counting techniques, error estimation, and the number of grains to be counted" authored by Jan Schönig and submitted to Journal of Geophysical Research: Earth Surface. Figure S1: Error of different counting methods in comparison with theory and without considering the finite population correction Table S1: Heavy-mineral dataset from semi-automated Raman analysis Table S2: Summary of heavy-mineral composition for individual samples in percent Table S3: Computed ribbon compositions for individual samples and ribbon sizes given in numbers of counts Table S4: Relative errors at 95 % quantile for consecutive ribbon counting simulations Table S5: Relative errors at 95 % quantile for maximum distance ribbon counting simulations Table S6: Relative errors at 95 % quantile for cluster counting simulations Table S7: Numerical solution for determining the number of counts required to discriminate the content of two mineral species in an aliquot