Non-Bayesian Confirmation Theory, and the Principle of Explanatory Surplus

Extract

One of the most obvious features of empirical science is that scientists attempt to relate their theories to data, that is to the results of observation and experiment. In so doing, they will find it necessary to use the term ‘confirms’ or ‘confirmation’ or at least terms with more or less the same meaning. Thus scientists may think that a theory is well- confirmed by a considerable body of observational evidence. In this case they will regard it as rational to have a high degree of confidence in the theory, and, in particular, to use it in practical applications. Alternatively a theory T may be seen as badly confirmed by the evidence. In this case it would be thought undesirable to use T in practice, and the problem would become that of modifying or replacing T so as to obtain a new theory T’ which is better confirmed than T.