Statistical Methods For Mineral Engineers !!better!! ❲ESSENTIAL — 2026❳

: Comparing mean values of two datasets (e.g., recovery before and after a reagent change).

A plant processing a complex sulfide ore used PCA on 25 QA/QC variables. Two components explained 78% of variance: PC1 (sulfide content) and PC2 (clay content). Monitoring just these two components instead of 25 separate charts simplified control. Statistical Methods For Mineral Engineers

p-value = 0.003 (<0.05). Reject H₀.

Practical Statistics for Process Optimization Target Audience: Metallurgists, Process Engineers, and Plant Managers. Core Value: Transforming noisy plant data into reliable process models. : Comparing mean values of two datasets (e

Statistical methods help quantify the inherent "noise" in mineral processing: Error Propagation Monitoring just these two components instead of 25

Traditional statistics treats data points as independent. Geostatistics, founded by Georges Matheron based on Danie Krige’s work in the South African gold mines, acknowledges that samples close together are more similar than samples far apart .