Probability and Evidence

Overview

In 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...
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Overview

In 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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Product Details

  • ISBN-13: 9780521283366
  • Publisher: Cambridge University Press
  • Publication date: 6/16/2011
  • Series: Cambridge Studies in Philosophy Series
  • Edition description: Reissue
  • Pages: 158
  • Product dimensions: 5.50 (w) x 8.40 (h) x 0.60 (d)

Table of Contents

Preface; Part I. Methodology: 1. Introduction; 2. Aspects of the scientific method; 3. A taste of Bayesianism; Part II. Probability: 4. The primitive theory; 5. Subjectivism; 6. The rationalist interpretation; 7. The logical interpretation; 8. The evidential state; 9. The empirical interpretation; Part III. Confirmation: 10. Explications; 11. The paradox; 12. A Bayesian pseudo-solution to the problem of induction; 13. Projection; Part IV. Induction; Section 1. The Nature of Inductive Inference; Section 2. Conditions of Rationality: 14. Demonstrable reliability; 15. The demonstrable reliability of c+; 16. Immodesty; 17. Audacity; Section 3. The Justification of Induction: 18. The impossibility of a noncircular rationale; 19. Inductive demonstration of reliability; 20. Semantic justification; Part V. Prediction: 21. Surprise; 22. Severe tests; 23. Ad hoc hypothesis; 24. Prediction versus accommodation; Part VI. Evidence: 25. The evidential value of varied data; 26. The value of further data; Part VII. Realism: 27. Popper; 28. Realism versus instrumentalism; 29. Putnam; 30. Glymour; 31. Conclusion; Bibliography; Index.
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