Abstract
Model building is at best a dynamic process where model fitting and analysis may lead to new experiments and an improved model. The language of statistics is often used for evaluation of models. Statistics, however, is the science of random errors and random errors are not the main problem for model builders. Removal of systematic errors is generally the major issue. Hence, the given confidence limits are often many times too small. The non-statistical errors may be of three kinds:
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Experimental errors
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Errors due to wrong model structure
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Errors due to wrong parameters
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Øye, H.A. (2002). Modelling of Thermodynamic Data. In: Gaune-Escard, M. (eds) Molten Salts: From Fundamentals to Applications. NATO Science Series, vol 52. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0458-9_6
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DOI: https://doi.org/10.1007/978-94-010-0458-9_6
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