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Foundations of Bayesianism

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Cover of 'Foundations of Bayesianism'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction: Bayesianism into the 21st Century
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    Chapter 2 Bayesianism and Causality, or, Why I am Only a Half-Bayesian
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    Chapter 3 Causal Inference without Counterfactuals
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    Chapter 4 Foundations for Bayesian Networks
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    Chapter 5 Probabilistic Learning Models
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    Chapter 6 The Logic of Bayesian Probability
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    Chapter 7 Subjectivism, Objectivism and Objectivity in Bruno de Finetti’s Bayesianism
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    Chapter 8 Bayesianism in Mathematics
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    Chapter 9 Common Sense and Stochastic Independence
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    Chapter 10 Integrating Probabilistic and Logical Reasoning
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    Chapter 11 Ramsey and the Measurement of Belief
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    Chapter 12 Bayesianism and Independence
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    Chapter 13 The Paradox of the Bayesian Experts
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    Chapter 14 Bayesian Learning and Expectations Formation: Anything Goes
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    Chapter 15 Bayesianism and the Fixity of the Theoretical Framework
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    Chapter 16 Principles of Inference and Their Consequences
Attention for Chapter 14: Bayesian Learning and Expectations Formation: Anything Goes
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