How do we go about weighing evidence, testing hypotheses, and making inferences? According to the model of Inference to the Best Explanation, we work out what to infer from the evidence by thinking about what would actually explain that evidence, and we take the ability of a hypothesis to explain the evidence as a sign that the hypothesis is correct. In Inference to the Best Explanation, Peter Lipton gives this important and influential idea the development and assessment it deserves.
The second edition has been substantially enlarged and reworked, with a new chapter on the relationship between explanation and Bayesianism, and an extension and defence of the account of contrastive explanation. It also includes an expanded defence of the claims that our inferences really are guided by diverse explanatory considerations, and that this pattern of inference can take us towards the truth. This edition of Inference to the Best Explanation has also been updated throughout and includes a new bibliography.
'The first edition of Peter Lipton's Inference to the Best Explanation, which appeared in 1991, is a modern classic in the philosophy of science. Yet in the second edition of the book, Lipton proves that even a classic can be improved … a 'must' read for anyone who wants a deeper understanding of inductive inference, broadly understood.' – Notre Dame Philosophical Reviews
'Peter Lipton's excellent book approaches the descriptive task with imagination and style. Lipton argues persuasively that an understanding of the workings of contrastive explanation can yield insight into our inferential practices.' – Times Literary Supplement
'Lipton makes valuable contributions with respect to any number of important questions in epistemology and philosophy of science. Anyone with more than a passing interest in these fields will find his book indispensable.' – The Philosophical Review
Preface to the Second Edition Preface to the First Edition Introduction 1. Induction 2. Explanation 3. The Causal Model 4. Inference to the Best Explanation 5. Contrastive Inference 6. The Raven Paradox 7. Bayesian Abduction 8. Explanation as a Guide to Inference 9. Loveliness and Truth 10. Prediction and Prejudice 11. Truth and Explanation Conclusion Bibliography Index