## Information, inference and decision |

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### Contents

gunter menges and heinz j skala On the Problem | 51 |

bernd leiner Notes on Etiality the Adaptation Criterion | 63 |

A s fraser Comparison of Inference Philosophies | 77 |

Copyright | |

7 other sections not shown

### Common terms and phrases

action analysis application background knowledge Bayes Boolean cardinal utility classical components concept conditional test consequence considered criterion decision function decision problem defined definition denote entropy etiality principle evidence example expected value experiment fiducial density finite Fisher Fraser fuzzy set Giinter Menges given hypothesis independence axiom inductive behaviour inductive logic Inference and Decision inference measure interpretation likelihood function loss function Marschak mathematical measure of information meta-rules methods objective theory observed obtained optimal outcome perfect information Poisson possible posterior probability posteriori preference relation priori distribution prob probability distribution probability measure probability theory probability1 properties proposition R. A. Fisher reference set respect sample SchneeweiB scientist Section semantic information sense of Carnap significance level Skala space Sprott statistical decision theory statistical inference Statistische Hefte Stegmuller structural theory subjective probability theorem theory of inductive tion trips true uncertainty unconditional University of Heidelberg utility function vagueness