Countless chemical measurements are performed worldwide each day and they rely not only on calibration standards and measurement methods but also on mathematical models. The choices analysts make about such models can have a significant effect on the reported measurement results. The challenge is therefore for analysts to explore the rich variety of modeling options, appreciate their effect on the results, and recognize that a larger statistical toolkit can raise the bar for more reliable results.
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