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No matter how irrefutable it may seem, evidence is often a matter of interpretation. Incomplete, inconclusive, imprecise, or vague, it is nonetheless the basis of myriad everyday conclusions and decisions. In this authoritative work, David A. Schum develops a general theory of evidence as it is understood and applied across a broad range of disciplines and practical undertakings. Synthesizing insights from law, philosophy and logic, probability, semiotics, artificial intelligence, psychology, and history, Schum provides a detailed examination of the various properties and uses of evidence and the evaluative skills evidence requires. Along with the evidential subtleties of probabilistic reasoning, Schum also explores the processes by which evidence is generated or discovered and looks at the intellectual and practical underpinnings of probabilistic reasoning. It is a useful resource for students, researchers, and practitioners of every discipline concerned with evidence and its inferential use.
Probabilities --- Evidence --- Inference
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Mathematical statistics --- Stochastic processes --- Inference --- Processus stochastiques --- Congresses. --- Congrès
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Mathematical statistics --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Statistical methods --- Statistique
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Since the publication of the first edition of this classic textbook over thirty years ago, tens of thousands of students have used A Course in Probability Theory. New in this edition is an introduction to measure theory that expands the market, as this treatment is more consistent with current courses. While there are several books on probability, Chung's book is considered a classic, original work in probability theory due to its elite level of sophistication.
Probabilities. --- Probability --- Statistical inference --- Combinations --- Mathematics --- Chance --- Least squares --- Mathematical statistics --- Risk --- UmU kursbok
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This research monograph on circular data analysis covers some recent advances in the field, besides providing a brief introduction to, and a review of, existing methods and models. The primary focus is on recent research into topics such as change-point problems, predictive distributions, circular correlation and regression, etc. An important feature of this work is the S-plus subroutines provided for analyzing actual data sets. Coupled with the discussion of new theoretical research, the book should benefit both the researcher and the practitioner.
Contents:
Circular data. --- Mathematical statistics. --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Data, Circular --- Statistical methods
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Choice (Psychology) --- Inference. --- Logic, Symbolic and mathematical. --- Nonmonotonic reasoning. --- Choice (Psychology). --- Inference --- Logic, Symbolic and mathematical --- Nonmonotonic reasoning --- Non-monotonic reasoning --- Algebra of logic --- Logic, Universal --- Mathematical logic --- Symbolic and mathematical logic --- Symbolic logic --- Ampliative induction --- Induction, Ampliative --- Inference (Logic) --- Reasoning --- Mathematics --- Algebra, Abstract --- Metamathematics --- Set theory --- Syllogism --- Psychology --- Logique mathématique --- Philosophie --- Artificial intelligence --- Logique --- Knowledge representation
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The idea that simplicity matters in science is as old as science itself, with the much cited example of Ockham's Razor, 'entia non sunt multiplicanda praeter necessitatem': entities are not to be multiplied beyond necessity. A problem with Ockham's razor is that nearly everybody seems to accept it, but few are able to define its exact meaning and to make it operational in a non-arbitrary way. Using a multidisciplinary perspective including philosophers, mathematicians, econometricians and economists, this 2002 monograph examines simplicity by asking six questions: what is meant by simplicity? How is simplicity measured? Is there an optimum trade-off between simplicity and goodness-of-fit? What is the relation between simplicity and empirical modelling? What is the relation between simplicity and prediction? What is the connection between simplicity and convenience? The book concludes with reflections on simplicity by Nobel Laureates in Economics.
Simplicity (Philosophy) --- Inference --- Econometrics --- Econometrics. --- Inference. --- Simplicity (Philosophy). --- Business, Economy and Management --- Economics --- Economics, Mathematical --- Statistics --- Ampliative induction --- Induction, Ampliative --- Inference (Logic) --- Reasoning --- Philosophy --- 117 --- 330.0151 --- 165.23 --- 330.115 --- 165.23 Kennis: begripsanalyse naar woordbetekenis; betekeningsvraagstuk --- Kennis: begripsanalyse naar woordbetekenis; betekeningsvraagstuk --- 330.115 Econometrie --- Econometrie
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Probabilities --- 519.2 --- Probability --- Statistical inference --- Combinations --- Mathematics --- Chance --- Least squares --- Mathematical statistics --- Risk --- Probability. Mathematical statistics --- 519.2 Probability. Mathematical statistics
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Mathematical statistics --- 519.22 --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Statistical theory. Statistical models. Mathematical statistics in general --- Statistical methods --- Mathematical statistics. --- 519.5 --- 519.22 Statistical theory. Statistical models. Mathematical statistics in general
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