Isbn: 9780521052429 - causal asymmetries (cambridge studies in probability, induction and decision theory) (6 Ergebnisse)

Paperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Paperback. Zustand: Very Good. Causal Asymmetries (Cambridge Studies in Probability, Induction and Decision Theory) This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping.…

Paperback. Zustand: Very Good. Shipped within 24 hours from our UK warehouse. Clean, undamaged book with no damage to pages and minimal wear to the cover. Spine still tight, in very good condition. Remember if you are not happy, you are covered by our 100% money back guarantee.

Zustand: New. In English.

Zustand: New. The most comprehensive account available of causal asymmetry, written by a pre-eminent philosopher of science. Series: Cambridge Studies in Probability, Induction and Decision Theory. Num Pages: 320 pages, 34 b/w illus. BIC Classification: HPL. Category: (P) Professional & Vocational. Dimension: 228 x 152 x 18. Weight in Grams: 470. . 2008. 1st Edition. paperback. . . . . Books ship from the US and Ireland. …

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book, by one of the pre-eminent philosophers of science writing today, offers the most comprehensive account available of causal asymmetries. Causation is asymmetrical in many different ways. Causes precede effects; explanations cite causes not effects. Agents use causes to manipulate their effects; they don't use effects to manipulate their causes. Effects of a common cause are correlated; causes of a common effect are not. This book explains why a relationship that is asymmetrical in one of these regards is asymmetrical in the others. Hausman discovers surprising hidden connections between theories of causation and traces them all to an asymmetry of independence. This is a major book for philosophers of science that will also prove insightful to economists and statisticians. …