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Philosophers of science in this period also thought that they had a clear view of scientific rationality: to be rational is to accept and reject hypotheses according to the rules of method, or perhaps to distribute degrees of confirmation in accordance with Bayesian standards.
Third and finally, degrees of confirmation should be understood in terms of probability.
This approach bypassed the issue in Peircian pragmatism of whether a scientific process of inquiry as justified by greater degrees of confirmation required the prior demonstration of the existence of an asymptotic "limit" for the process.
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Carnap granted the importance of this concept (especially in modern physical theories) but attempted, in increasingly refined and often revised forms, to define a concept of degree-of-confirmation that was purely logical.
The degree to which \(E\) confirms \(H\), called the degree of confirmation, is written \(c(H,E \) and is defined: \[c(H,E) = p(H\mid E) - p(H).\] When \(c(H,E \) is negative, \(E\) actually decreases the probability of \(H\), and we say that \(E\) disconfirms \(H\).
when m e) > 0, for the degree of confirmation of the hypothesis h on evidence e. Degree of confirmation satisfies the laws of probability and in addition symmetry.
There is no general agreement in the literature on a quantitative measure of degree of confirmation or degree of evidential support.
Carnap is interested in determining the degree of confirmation of a hypothesis relative to a given set of observations.
On its face, a single notion of degree of confirmation does not apply in different contexts of inquiry.
Thus, the rule "Always accept the theory with the greatest degree of confirmation" would count as (part of) a methodology.
It can be shown that in general m* yields a degree of confirmation c* that allows learning from experience.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com