Probability and EvidenceIn this volume, which was originally published in 1982, Paul Horwich presents a clear and unified approach to a number of problems in the philosophy of science. He diagnoses the failure of other attempts to resolve them as stemming from a too-rigid, all-or-nothing conception of belief, and adopts instead a Bayesian strategy, emphasising the degree of confidence to which we are entitled the light of scientific evidence. This probabilistic approach, he argues, yields a more complete understanding of the assumptions and procedures characteristic of scientific reasoning. It also accounts for the merits of simplicity, severe tests and surprising predictions, and provides a way in which the dispute between the realist and instrumentalist views of science might be resolved. The result is a crisp, well-focused contribution to the philosophy of science. The elaboration of an important conception of probability will stimulate anyone with an interest in the field. |
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accept accommodation according alternative approach argument assign assume assumption Bayesian better c-function circumstances claims coin concept concerning conclusion condition confirmation consequences consider consists constraints credibility degree of belief demonstrable depends determine discovered discovery emeralds empirical entails equal evidence evidential example existence expected explain fact false follows formulated frequency function further given greater green heads hypothesis idea inductive practice inference intuition involve justified known limit logical Mars matter means method natural object observation paradox particular philosophy plausible points positive possible prediction principles prior probability problem proportion proposed question rational raven realism reason relative reliability represent requirement satisfy scientific seems sequence simply specified statements subjective probability sufficient suggest suppose surprising theorem theory things tion true truth val iff various worlds yield