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Road from Geochemistry to Geochemometrics pp 403–422Cite as

Bivariate Data and Calibration of Experimental Systems

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Abstract

In this chapter, statistical methodology for bivariate data and calibration of experimental systems is developed. Experimental systems include analytical instruments useful in geochemistry. From the freely available BiDASys software, we can apply both the conventional ordinary least-squares linear regression (OLR) and the new uncertainty weighted least-squares linear regression (UWLR) models. BiDASys was used for achieving and comparing the OLR and UWLR models for the calibration of a high-performance liquid chromatography equipment for the determination of rare-earth elements. Equations are provided for both regressions. The advantages of the UWLR model over the OLR are clearly documented. This is followed by linearity tests, which are useful for deciding whether a linear or a curvilinear fit is more appropriate. ANOVA for the evaluation of fitting is finally presented and exemplified from citations of literature on new precise and accurate critical values for the F and t tests.

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Authors and Affiliations

  1. Instituto de Energías Renovables, Universidad Nacional Autónoma de México, Temixco, Mexico

    Surendra P. Verma

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Correspondence to Surendra P. Verma .

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Verma, S.P. (2020). Bivariate Data and Calibration of Experimental Systems. In: Road from Geochemistry to Geochemometrics. Springer, Singapore. https://doi.org/10.1007/978-981-13-9278-8_9

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