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The design inference : eliminating chance through small probabilities / William A. Dembski
Material type:
TextSeries: Cambridge studies in probability, induction, and decision theoryDescription: xvii, 243 pages : illustrations ; 23 cmISBN: - 0521623871
- 9780521623872
- ARCH YNDC 001.4 D375D 21
- QA279 .D455 1998
- BD581 .D455 1998
Contents:
Summary: How can we identify events due to intelligent causes and distinguish them from events due to undirected natural causes? If we lack a causal theory how can we determine whether an intelligent cause acted? This book presents a reliable method for detecting intelligent causes: the design inference. The design inference uncovers intelligent causes by isolating the key trademark of intelligent causes: specified events of small probability. Design inferences can be found in a range of scientific pursuits from forensic science to research into the origins of life to the search for extraterrestrial intelligence. This challenging and provocative book will be read with particular interest by philosophers of science and religion, other philosophers concerned with epistemology and logic, probability and complexity theorists, and statisticians
I. Introduction : Historical overview -- The man with the golden arm -- Intellectual property protection -- Forensic science and detection -- Data falsification in science -- Cryptography (and SETI) -- Randomness -- II. Overview of the design inference : The explanatory filter -- The logic of the inference -- Case study, the creation-evolution controversy -- From design to agency -- III. Probability theory : The probability of an event -- Events -- Background information -- Likelihood -- The best available estimate -- Axiomization of probability -- IV. Complexity theory : The complexity of a problem -- Problems and resources -- Difficulty and its estimation -- Axiomization of complexity -- Calibration through complexity bounds -- Information measures -- RMS measures -- Technical supplement on RMS measure -- V. SSpecification : Patterns -- The requisite precondition -- Detachability -- Specification defined -- Pyramids and presidents -- Information tucked within information -- Prediction -- Increasing the power of a complexity measure -- Caputo revisited -- Randomness revisited -- VI. Small probability : Probabilistic resources -- The generic chance elimination argument -- The magic number 1/2 -- Statistical signigcance testing -- Local and universal small probabilities -- The inflationary fallacy -- The law of small probability
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SAIACS Archives Room | Yandell Collection | ARCH YNDC 001.4 D375D (Browse shelf(Opens below)) | Not for loan | 064826 |
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Includes bibliographical references (pages 231-238) and index
I. Introduction : Historical overview -- The man with the golden arm -- Intellectual property protection -- Forensic science and detection -- Data falsification in science -- Cryptography (and SETI) -- Randomness -- II. Overview of the design inference : The explanatory filter -- The logic of the inference -- Case study, the creation-evolution controversy -- From design to agency -- III. Probability theory : The probability of an event -- Events -- Background information -- Likelihood -- The best available estimate -- Axiomization of probability -- IV. Complexity theory : The complexity of a problem -- Problems and resources -- Difficulty and its estimation -- Axiomization of complexity -- Calibration through complexity bounds -- Information measures -- RMS measures -- Technical supplement on RMS measure -- V. SSpecification : Patterns -- The requisite precondition -- Detachability -- Specification defined -- Pyramids and presidents -- Information tucked within information -- Prediction -- Increasing the power of a complexity measure -- Caputo revisited -- Randomness revisited -- VI. Small probability : Probabilistic resources -- The generic chance elimination argument -- The magic number 1/2 -- Statistical signigcance testing -- Local and universal small probabilities -- The inflationary fallacy -- The law of small probability
How can we identify events due to intelligent causes and distinguish them from events due to undirected natural causes? If we lack a causal theory how can we determine whether an intelligent cause acted? This book presents a reliable method for detecting intelligent causes: the design inference. The design inference uncovers intelligent causes by isolating the key trademark of intelligent causes: specified events of small probability. Design inferences can be found in a range of scientific pursuits from forensic science to research into the origins of life to the search for extraterrestrial intelligence. This challenging and provocative book will be read with particular interest by philosophers of science and religion, other philosophers concerned with epistemology and logic, probability and complexity theorists, and statisticians
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