Ian Hacking is the winner of the Holberg International Memorial Prize 2009.

'Hacking's book excels … especially in the practical, concrete examples. It uses minimal mathematics and presumes no acquaintance with symbolic logic. It is well suited for graduate or advanced undergraduate courses in inductive logic or related areas (such as philosophy of science or methodology courses in particular empirical sciences). The book gives a nice introduction to inductive logic.' Harry Gensler, The Times Higher Education Supplement

• Part I. Logic: 1. Logic; 2. What is inductive logic?; Part II. How to Calculate Probabilities: 3. The gambler's fallacy; 4. Elementary probability; 5. Conditional probability; 6. Basic laws of probability; 7. Bayes' rule; Part III. How to Combine Probabilities and Utilities: 8. Expected value; 9. Maximizing expected value; 10. Decision under uncertainty; Part IV. Kinds of Probability: 11. What do you mean?; 12. Theories about probability; Part V. Probability as a Measure of Belief: 13. Personal probabilities; 14. Coherence; 15. Learning from experience; Part VI. Probability as Frequency: 16. Stability; 17. Normal approximations; 18. Significance; 19. Confidence and inductive behaviour; Part VII. Probability Applied to Philosophy: 20. The philosophical problem of induction; 21. Learning from experience as an evasion of the problem; 22. Inductive behaviour as an evasion of the problem.

Ian Hacking is the winner of the Holberg International Memorial Prize 2009.

'Hacking's book excels … especially in the practical, concrete examples. It uses minimal mathematics and presumes no acquaintance with symbolic logic. It is well suited for graduate or advanced undergraduate courses in inductive logic or related areas (such as philosophy of science or methodology courses in particular empirical sciences). The book gives a nice introduction to inductive logic.' Harry Gensler, The Times Higher Education Supplement

• Part I. Logic: 1. Logic; 2. What is inductive logic?; Part II. How to Calculate Probabilities: 3. The gambler's fallacy; 4. Elementary probability; 5. Conditional probability; 6. Basic laws of probability; 7. Bayes' rule; Part III. How to Combine Probabilities and Utilities: 8. Expected value; 9. Maximizing expected value; 10. Decision under uncertainty; Part IV. Kinds of Probability: 11. What do you mean?; 12. Theories about probability; Part V. Probability as a Measure of Belief: 13. Personal probabilities; 14. Coherence; 15. Learning from experience; Part VI. Probability as Frequency: 16. Stability; 17. Normal approximations; 18. Significance; 19. Confidence and inductive behaviour; Part VII. Probability Applied to Philosophy: 20. The philosophical problem of induction; 21. Learning from experience as an evasion of the problem; 22. Inductive behaviour as an evasion of the problem.