Bayes Or Bust
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Bayes Or Bust
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Author : John Earman
language : en
Publisher: Bradford Books
Release Date : 1992
Bayes Or Bust written by John Earman and has been published by Bradford Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Psychology categories.
There is currently no viable alternative to the Bayesian analysis of scientific inference, yet the available versions of Bayesianism fail to do justice to several aspects of the testing and confirmation of scientific hypotheses. Bayes or Bust? provides the first balanced treatment of the complex set of issues involved in this nagging conundrum in the philosophy of science. Both Bayesians and anti-Bayesians will find a wealth of new insights on topics ranging from Bayes's original paper to contemporary formal learning theory. In a paper published posthumously in 1763, the Reverend Thomas Bayes made a seminal contribution to the understanding of "analogical or inductive reasoning." Building on his insights, modem Bayesians have developed an account of scientific inference that has attracted numerous champions as well as numerous detractors. Earman argues that Bayesianism provides the best hope for a comprehensive and unified account of scientific inference, yet the presently available versions of Bayesianisin fail to do justice to several aspects of the testing and confirming of scientific theories and hypotheses. By focusing on the need for a resolution to this impasse, Earman sharpens the issues on which a resolution turns. John Earman is Professor of History and Philosophy of Science at the University of Pittsburgh.
Inference Explanation And Other Frustrations
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Author : John Earman
language : en
Publisher: Univ of California Press
Release Date : 2023-07-28
Inference Explanation And Other Frustrations written by John Earman and has been published by Univ of California Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-28 with Philosophy categories.
These provocative essays by leading philosophers of science exemplify and illuminate the contemporary uncertainty and excitement in the field. The papers are rich in new perspectives, and their far-reaching criticisms challenge arguments long prevalent in classic philosophical problems of induction, empiricism, and realism. By turns empirical or analytic, historical or programmatic, confessional or argumentative, the authors' arguments both describe and demonstrate the fact that philosophy of science is in a ferment more intense than at any time since the heyday of logical positivism early in the twentieth century. Contents: “Thoroughly Modern Meno,” Clark Glymour and Kevin Kelly “The Concept of Induction in the Light of the Interrogative Approach to Inquiry,” Jaakko Hintikka “Aristotelian Natures and Modern Experimental Method,” Nancy Cartwright “Genetic Inference: A Reconsideration of “David Hume's Empiricism,” Barbara D. Massey and Gerald J. Massey “Philosophy and the Exact Sciences: Logical Positivism as a Case Study,” Michael Friedman “Language and Interpretation: Philosophical Reflections and Empirical Inquiry,” Noam Chomsky “Constructivism, Realism, and Philosophical Method,” Richard Boyd “Do We Need a Hierarchical Model of Science?” Diderik Batens “Theories of Theories: A View from Cognitive Science,” Richard E. Grandy “Procedural Syntax for Theory Elements,” Joseph D. Sneed “Why Functionalism Didn't Work,” Hilary Putnam “Physicalism,” Hartry Field This title is part of UC Press's Voices Revived program, which commemorates University of California Press’s mission to seek out and cultivate the brightest minds and give them voice, reach, and impact. Drawing on a backlist dating to 1893, Voices Revived makes high-quality, peer-reviewed scholarship accessible once again using print-on-demand technology. This title was originally published in 1992.
Bayes Theorem And Bayesian Statistics
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Author : Lee Baker
language : en
Publisher: Lee Baker
Release Date :
Bayes Theorem And Bayesian Statistics written by Lee Baker and has been published by Lee Baker this book supported file pdf, txt, epub, kindle and other format this book has been release on with Medical categories.
Bayes’ Theorem is hard. Is it, though? If you flick through any of the other books on Bayesian statistics you’ll get the distinct impression that you’ll have a lot of really hard maths to do, and it can be really intimidating. But is that what Bayesian stats is really all about? If you’re wondering whether you should have a look at Bayesian statistics to see if it’s right for you, then Bayes’ Theorem and Bayesian Statistics in the Getting Started With Statistics series is your first port of call. If what you need is a short guide to getting started, a snappy little non-threatening introduction to Bayes’ Theorem and Bayesian Statistics that dispels the biggest myths, answers the most frequently asked questions and inspires you to take the next steps in your journey, then look no further. Bayes’ Theorem and Bayesian Statistics is that guide. This book is not written for statisticians. Nor is it written by a statistician. A Physicist by trade, and a self-taught statistician, I may have worked (and taught) as a statistician for several years but I have my own struggles with statistics, so I understand where the hard bits are. Better still, I know how to explain them to others in plain English without using difficult to understand technical terminology. That’s what you can expect in this book. First, I’ll explain what Bayes’ Theorem is in simple terms. Then you’ll move on to understanding what conditional probability is and why you don’t need it if you want to find a parking spot, but you do if you’re playing cards (and you want to win). You’ll learn about Prior and Posterior probabilities, and use them to work out if you need to take a brolly to the beach with you (spoiler alert – I live in Scotland. I always need to take a brolly to the beach!). Then I’ll bust a few myths about what Bayesian statistics is – and what it isn’t. By this point you’ll have made up your mind about whether you want to go further, so I’ll show you how to take your next steps. Bayes’ Theorem and Bayesian Statistics makes no assumptions about your previous experience and is perfect for beginners and the Bayes-curious! Discover the world of Bayes’ Theorem and Bayesian Statistics. Get this book, TODAY!
Theories Of Scientific Method
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Author : Robert Nola
language : en
Publisher: Routledge
Release Date : 2014-12-18
Theories Of Scientific Method written by Robert Nola and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-18 with Philosophy categories.
What is it to be scientific? Is there such a thing as scientific method? And if so, how might such methods be justified? Robert Nola and Howard Sankey seek to provide answers to these fundamental questions in their exploration of the major recent theories of scientific method. Although for many scientists their understanding of method is something they just pick up in the course of being trained, Nola and Sankey argue that it is possible to be explicit about what this tacit understanding of method is, rather than leave it as some unfathomable mystery. They robustly defend the idea that there is such a thing as scientific method and show how this might be legitimated. This book begins with the question of what methodology might mean and explores the notions of values, rules and principles, before investigating how methodologists have sought to show that our scientific methods are rational. Part 2 of this book sets out some principles of inductive method and examines its alternatives including abduction, IBE, and hypothetico-deductivism. Part 3 introduces probabilistic modes of reasoning, particularly Bayesianism in its various guises, and shows how it is able to give an account of many of the values and rules of method. Part 4 considers the ideas of philosophers who have proposed distinctive theories of method such as Popper, Lakatos, Kuhn and Feyerabend and Part 5 continues this theme by considering philosophers who have proposed naturalised theories of method such as Quine, Laudan and Rescher. This book offers readers a comprehensive introduction to the idea of scientific method and a wide-ranging discussion of how historians of science, philosophers of science and scientists have grappled with the question over the last fifty years.
Bayesian Nets And Causality Philosophical And Computational Foundations
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Author : Jon Williamson
language : en
Publisher: Oxford University Press
Release Date : 2005
Bayesian Nets And Causality Philosophical And Computational Foundations written by Jon Williamson and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Computers categories.
Bayesian nets are used in artificial intelligence as a calculus for causal reasoning, enabling machines to make predictions perform diagnoses, take decisions and even to discover causal relationships. This book brings together how to automate reasoning in artificial intelligence, and the nature of causality and probability in philosophy.
A Student S Guide To Bayesian Statistics
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Author : Ben Lambert
language : en
Publisher: SAGE
Release Date : 2018-04-20
A Student S Guide To Bayesian Statistics written by Ben Lambert and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-20 with Social Science categories.
Supported by a wealth of learning features, exercises, and visual elements as well as online video tutorials and interactive simulations, this book is the first student-focused introduction to Bayesian statistics. Without sacrificing technical integrity for the sake of simplicity, the author draws upon accessible, student-friendly language to provide approachable instruction perfectly aimed at statistics and Bayesian newcomers. Through a logical structure that introduces and builds upon key concepts in a gradual way and slowly acclimatizes students to using R and Stan software, the book covers: An introduction to probability and Bayesian inference Understanding Bayes′ rule Nuts and bolts of Bayesian analytic methods Computational Bayes and real-world Bayesian analysis Regression analysis and hierarchical methods This unique guide will help students develop the statistical confidence and skills to put the Bayesian formula into practice, from the basic concepts of statistical inference to complex applications of analyses.
Bayesian Rationality
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Author : Mike Oaksford
language : en
Publisher: Oxford University Press
Release Date : 2007-02-22
Bayesian Rationality written by Mike Oaksford and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-02-22 with Philosophy categories.
For almost 2,500 years, the Western concept of what is to be human has been dominated by the idea that the mind is the seat of reason - humans are, almost by definition, the rational animal. In this text a more radical suggestion for explaining these puzzling aspects of human reasoning is put forward.
Bayesian Philosophy Of Science
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Author : Jan Sprenger
language : en
Publisher:
Release Date : 2019-08-15
Bayesian Philosophy Of Science written by Jan Sprenger and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-15 with Bayesian statistical decision theory categories.
How should we reason in science? Jan Sprenger and Stephan Hartmann offer a refreshing take on classical topics in philosophy of science, using a single key concept to explain and to elucidate manifold aspects of scientific reasoning. They present good arguments and good inferences as beingcharacterized by their effect on our rational degrees of belief. Refuting the view that there is no place for subjective attitudes in "objective science", Sprenger and Hartmann explain the value of convincing evidence in terms of a cycle of variations on the theme of representing rational degrees ofbelief by means of subjective probabilities (and changing them by Bayesian conditionalization). In doing so, they integrate Bayesian inference - the leading theory of rationality in social science - with the practice of 21st century science.Bayesian Philosophy of Science thereby shows how modeling such attitudes improves our understanding of causes, explanations, confirming evidence, and scientific models in general. It combines a scientifically minded and mathematically sophisticated approach with conceptual analysis and attention tomethodological problems of modern science, especially in statistical inference, and is therefore a valuable resource for philosophers and scientific practitioners.
Inference To The Best Explanation
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Author : Peter Lipton
language : en
Publisher: Taylor & Francis
Release Date : 2004
Inference To The Best Explanation written by Peter Lipton and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Philosophy categories.
Inference to the Best Explanation is an unrivalled exposition of a theory of particular interest to students both of epistemology and the philosophy of science.
The Philosophy Of Quantitative Methods
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Author : Brian D. Haig
language : en
Publisher: Oxford University Press
Release Date : 2018-01-04
The Philosophy Of Quantitative Methods written by Brian D. Haig and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-04 with Psychology categories.
The Philosophy of Quantitative Methods focuses on the conceptual foundations of research methods within the behavioral sciences. In particular, it undertakes a close philosophical examination of a variety of quantitative research methods that are prominent in (or relevant for) the conduct of research in these fields. By doing so, the deep structure of these methods is examined in order to overcome the non-critical approaches typically found in the existing literature today. In this book, Brian D. Haig focuses on the more well-known research methods such as exploratory data analysis, statistical significant testing, Bayesian confirmation theory and statistics, meta-analysis, and exploratory factor analysis. These methods are then examined with a philosophy consistent of scientific realism. In addition, each chapter provides a helpful Further Reading section in order to better assist the reader in extending their own thinking and research methods specific to their needs.