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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accommodation alternative argument B-worlds Bayes Bayesian belief in H c-function Carnap Carnapian characterisation coherence coin concept conclusion conditional degree confirmation function confirms H constraints credibility degree of belief degree of confirmation demonstrable reliability disconfirmed discovery emeralds are green empirical probability epistemological realism equal evidential circumstances evidential value example expected value fact false formulated further given grue H₁ Hempel's hoc hypotheses hypothesis inductive practice inductive reasoning inference intuition land heads logical probability Mars object observation outcome P(BR paradox particular phlogiston plausible prediction principle of indifference principles prior probability Prob probabilistic probability calculus probability claims probability theory problem of induction question rational rationalist ravens are black realism recognise relative frequency requirement of demonstrable sampled scientific methodology sequence severe tests Snell's law specified statements subjective probability suppose surprising theorem theory things tion total evidence true truth value unsampled val iff