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Philosophy Cambridge Mellor Probability Introduction

Articles by |
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edited by |
D. H. Mellor



A Philosophical Introduction

Probability:
A Philosophical Introduction

D. H. Mellor

London:
Routledge
2005, pp. xi+152



This book introduces and explains the principal concepts and applications of probability. It is for philosophers and others who want to understand probability as we apply it in our working and everyday lives. The role of probability in modern theories of knowledge, inference, induction, causation, laws of nature, action and decision-making makes an understanding of it especially important to philosophers and students of philosophy, for whom the book is intended both as a textbook and a work of reference. (It is however not a course in mathematical probability, of which it uses only the simplest results.) The book distinguishes the three basic kinds of probability - physical, epistemic, and subjective - and introduces and assesses the main theories and interpretations of them. The topics and concepts covered include chance, frequency, possibility, propensity, credence, confirmation and Bayesianism.

Review in Mind 115 (2006), 773-7
Review in Theoria 70 (2011), 99-103


Preface
Introduction and Summary

1 Kinds of Probability
1. Introduction
2. Chances
3. Epistemic Probabilities
4. Credences
5. How Kinds of Probability Differ
6. Probabilities of Complex Propositions
7. Conditional Probabilities
8. Numerical Probabilities
9. Pure and Applied Probability
2 Classical Probabilities
1. Introduction
2. Two Kinds of Possibility
3. Credences
4. Sample Spaces
5. Infinite Sample Spaces
6. Indifference
7. Chances
3 Frequencies
1. Credences
2. Epistemic Probabilities
3. Humean Chances
4. Frequentism and Classicism
5. Limiting Frequencies
6. Hypothetical Frequencies
4 Possibilities and Propensities
1. Modal Chances
2. Propensities
3. Dispositions
4. Dispositional Chances
5. Chance and Necessity
6. Modality versus Propensity
7. The Existence of Chances
5 Credence
1. Degrees of Belief
2. Betting and Belief
3. Coherence
4. Approximate Credences
5. Decision Theory
6 Confirmation
1. Measuring Evidential Support
2. Epistemic and Other Probabilities
3. Inductive Logic
4. Chances as Evidence
5. Confirmation Relations
7 Conditionalisation
1. Conditional Probability
2. The Pro Rata Rule
3. Epistemic Probabilities
4. Problems with Priors
5. Prior Credences
6. Bayes's Theorem
7. Bayesianism
8 Input Credences
1. Perception
2. Consistency
3. Reliability
4. Uncertain Evidence
9 Questions for Bayesians
1. Sample Spaces
2. Bayes's Proposition 3
3. Decisions and Credences
4. Conditional Bets
5. Imaging
6. Non-Bayesian Behaviour
7. Conclusion
10 Chance, Frequency and Credence
1. The Straight Rule
2. The Large Numbers Link
3. Independence
4. Chances and Estimates
5. Exchangeability
6. Frequencies and Credences
7. Subjectivism

References
Index


Updated 12 September 2019