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Figure 2
Different ways in which a model or hypothesis can be validated. Firstly, the input to the model itself (prior knowledge and experimental observations) needs to be validated. Secondly, the model or hypothesis should fit in with the prior knowledge and explain the experimental observations (thin arrows). However, the reliability or accuracy of a model is most convincingly demonstrated by its predictive quality with respect to data and information that were not used in the construction of the model (fat arrows). This may entail comparison to new or unused general prior knowledge, to independent observations pertaining to the system under study and to the results of experiments that were designed based on the model.

Journal logoBIOLOGICAL
CRYSTALLOGRAPHY
ISSN: 1399-0047
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