The dependability of a model is determined by its validity, the way it is well-founded. The quality of the foundations of a model becomes obvious in certain degrees depending on the evidence available to the modeller. There may be observations in favour of a model, thus supporting and confirming it, and there may be observations not in concordance with a model. The latter will certainly reduce the belief in the dependability of a model and cast doubt on it; in the worst case its futility will be proved and it will be refuted. This information will help us to induce a belief in the dependability of a model, which can be measured in degrees. This does not mean that we trust to a model blindly, but that our evaluation is founded on evidence and induced from experience gained from experiments. It is thus a degree of rational belief and may be quantified in terms of probability.
KeywordsPrior Probability Bayesian Inference Maximum Likelihood Method Initial Probability Rational Belief
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