Statistics Science Foundations Statistical (44 results)
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Hardcover. Condition: Near Fine. Dust Jacket Condition: Near Fine. 1st Edition. ix, 184 pp. Original cloth. Near Fine, in dust jacket. Boston Studies in the Philosophy and History of Science, 122. An inference may be defined as a passage of thought according to some method. In the theory of knowledge it is customary to distingui…sh deductive and non-deductive inferences. Deductive inferences are truth preserving, that is, the truth of the premises is preserved in the con clusion. As a result, the conclusion of a deductive inference is already 'contained' in the premises, although we may not know this fact until the inference is performed. Standard examples of deductive inferences are taken from logic and mathematics. Non-deductive inferences need not preserve truth, that is, 'thought may pass' from true premises to false conclusions. Such inferences can be expansive, or, ampliative in the sense that the performances of such inferences actually increases our putative knowledge. Standard non-deductive inferences do not really exist, but one may think of elementary inductive inferences in which conclusions regarding the future are drawn from knowledge of the past. Since the body of scientific knowledge is increasing, it is obvious that the method of science must allow non-deductive as well as deductive inferences. Indeed, the explosive growth of science in recent times points to a prominent role for the former. Philosophers of science have long tried to isolate and study the non-deductive inferences in science. The inevitability of such inferences one the one hand, juxtaposed with the poverty of all efforts to identify them, constitutes one of the major cognitive embarrassments of our time. Table of contents (10 chapters) Method, Theory, and Statistics: The Lesson of Physics Lorenz Krüger Pages 1-13 The Theory of Natural Selection as a Null Theory Abner Shimony Pages 15-26 Causality and Exogeneity in Econometric Models Maria Carla Galavotti, Guido Gambetta Pages 27-40 Statistics in Expert Resolution: A Theory of Weights for Combining Expert Opinion Roger M. Cooke Pages 41-72 Short and Long Term Survival Analysis in Oncological Research Ettore Marubini Pages 73-87 A statistical Approach to the Study of Pollen Fitness T. Caliński, E. Ottaviano, M. Sari Gorla Pages 89-101 Statistics in Genetics: Human Migrations Detected by Multivariate Techniques Alberto Piazza Pages 103-118 Quantum Probability and The Foundations of Quantum Theory Luigi Accardi Pages 119-147 Indistinguishability, Interchangeability, and Indeterminism Alexander Bach Pages 149-166 The Non Frequency Approach to Elementary Particle Statistics Domenico Costantini, Ubaldo Garibaldi Pages 167-181.
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Foundations of Bayesian Statistics for Data Scientists (Chapman & Hall/CRC Texts in Statistical Science)
Agresti, Alan; Kateri, Maria; Grove, Ranjini; Mira, Antonietta
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Foundations of Bayesian Statistics for Data Scientists: With R and Python (Chapman & Hall/CRC Texts in Statistical Science)
Agresti, Alan; Kateri, Maria; Grove, Ranjini; Mira, Antonietta
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Foundations of Bayesian Statistics for Data Scientists: With R and Python (Chapman & Hall/CRC Texts in Statistical Science)
Agresti, Alan Alan Agresti, Maria Kateri, Ranjini Grove, Antonietta Mira,
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Foundations of Bayesian Statistics for Data Scientists: With R and Python (Chapman & Hall/CRC Texts in Statistical Science)
Agresti, Alan; Kateri, Maria; Grove, Ranjini; Mira, Antonietta
Language: English
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Foundations of Bayesian Statistics for Data Scientists: With R and Python (Chapman & Hall/CRC Texts in Statistical Science)
Agresti, Alan; Kateri, Maria; Grove, Ranjini; Mira, Antonietta
Language: English
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - An inference may be defined as a passage of thought according to some method. In the theory of knowledge it is customary to distinguish deductive and non-deductive inferences. Deductive inferences are truth preserving, that is, the truth of the pre…mises is preserved in the con clusion. As a result, the conclusion of a deductive inference is already 'contained' in the premises, although we may not know this fact until the inference is performed. Standard examples of deductive inferences are taken from logic and mathematics. Non-deductive inferences need not preserve truth, that is, 'thought may pass' from true premises to false conclusions. Such inferences can be expansive, or, ampliative in the sense that the performances of such inferences actually increases our putative knowledge. Standard non-deductive inferences do not really exist, but one may think of elementary inductive inferences in which conclusions regarding the future are drawn from knowledge of the past. Since the body of scientific knowledge is increasing, it is obvious that the method of science must allow non-deductive as well as deductive inferences. Indeed, the explosive growth of science in recent times points to a prominent role for the former. Philosophers of science have long tried to isolate and study the non-deductive inferences in science. The inevitability of such inferences one the one hand, juxtaposed with the poverty of all efforts to identify them, constitutes one of the major cognitive embarrassments of our time.
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Published by Taylor & Francis Group, 2021
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