Error And Inference
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Error And Inference
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Author : Deborah G. Mayo
language : en
Publisher: Cambridge University Press
Release Date : 2009-10-26
Error And Inference written by Deborah G. Mayo and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-10-26 with Science categories.
Although both philosophers and scientists are interested in how to obtain reliable knowledge in the face of error, there is a gap between their perspectives that has been an obstacle to progress. By means of a series of exchanges between the editors and leaders from the philosophy of science, statistics and economics, this volume offers a cumulative introduction connecting problems of traditional philosophy of science to problems of inference in statistical and empirical modelling practice. Philosophers of science and scientific practitioners are challenged to reevaluate the assumptions of their own theories - philosophical or methodological. Practitioners may better appreciate the foundational issues around which their questions revolve and thereby become better 'applied philosophers'. Conversely, new avenues emerge for finally solving recalcitrant philosophical problems of induction, explanation and theory testing.
Statistical Inference As Severe Testing
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Author : Deborah G. Mayo
language : en
Publisher: Cambridge University Press
Release Date : 2018-09-20
Statistical Inference As Severe Testing written by Deborah G. Mayo and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-20 with Mathematics categories.
Unlock today's statistical controversies and irreproducible results by viewing statistics as probing and controlling errors.
Error And The Growth Of Experimental Knowledge
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Author : Deborah G. Mayo
language : en
Publisher: University of Chicago Press
Release Date : 1996-07-15
Error And The Growth Of Experimental Knowledge written by Deborah G. Mayo and has been published by University of Chicago Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-07-15 with Mathematics categories.
Preface1: Learning from Error 2: Ducks, Rabbits, and Normal Science: Recasting the Kuhn's-Eye View of Popper 3: The New Experimentalism and the Bayesian Way 4: Duhem, Kuhn, and Bayes 5: Models of Experimental Inquiry 6: Severe Tests and Methodological Underdetermination7: The Experimental Basis from Which to Test Hypotheses: Brownian Motion8: Severe Tests and Novel Evidence 9: Hunting and Snooping: Understanding the Neyman-Pearson Predesignationist Stance10: Why You Cannot Be Just a Little Bit Bayesian 11: Why Pearson Rejected the Neyman-Pearson (Behavioristic) Philosophy and a Note on Objectivity in Statistics12: Error Statistics and Peircean Error Correction 13: Toward an Error-Statistical Philosophy of Science ReferencesIndex Copyright © Libri GmbH. All rights reserved.
Principles Of Statistical Inference
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Author : D. R. Cox
language : en
Publisher: Cambridge University Press
Release Date : 2006-08-10
Principles Of Statistical Inference written by D. R. Cox and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-08-10 with Mathematics categories.
In this definitive book, D. R. Cox gives a comprehensive and balanced appraisal of statistical inference. He develops the key concepts, describing and comparing the main ideas and controversies over foundational issues that have been keenly argued for more than two-hundred years. Continuing a sixty-year career of major contributions to statistical thought, no one is better placed to give this much-needed account of the field. An appendix gives a more personal assessment of the merits of different ideas. The content ranges from the traditional to the contemporary. While specific applications are not treated, the book is strongly motivated by applications across the sciences and associated technologies. The mathematics is kept as elementary as feasible, though previous knowledge of statistics is assumed. The book will be valued by every user or student of statistics who is serious about understanding the uncertainty inherent in conclusions from statistical analyses.
Essential Statistical Inference
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Author : Dennis D. Boos
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-02-06
Essential Statistical Inference written by Dennis D. Boos and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-02-06 with Mathematics categories.
This book is for students and researchers who have had a first year graduate level mathematical statistics course. It covers classical likelihood, Bayesian, and permutation inference; an introduction to basic asymptotic distribution theory; and modern topics like M-estimation, the jackknife, and the bootstrap. R code is woven throughout the text, and there are a large number of examples and problems. An important goal has been to make the topics accessible to a wide audience, with little overt reliance on measure theory. A typical semester course consists of Chapters 1-6 (likelihood-based estimation and testing, Bayesian inference, basic asymptotic results) plus selections from M-estimation and related testing and resampling methodology. Dennis Boos and Len Stefanski are professors in the Department of Statistics at North Carolina State. Their research has been eclectic, often with a robustness angle, although Stefanski is also known for research concentrated on measurement error, including a co-authored book on non-linear measurement error models. In recent years the authors have jointly worked on variable selection methods.
Big Data And Social Science
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Author : Ian Foster
language : en
Publisher: CRC Press
Release Date : 2020-11-17
Big Data And Social Science written by Ian Foster and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-17 with Mathematics categories.
Big Data and Social Science: Data Science Methods and Tools for Research and Practice, Second Edition shows how to apply data science to real-world problems, covering all stages of a data-intensive social science or policy project. Prominent leaders in the social sciences, statistics, and computer science as well as the field of data science provide a unique perspective on how to apply modern social science research principles and current analytical and computational tools. The text teaches you how to identify and collect appropriate data, apply data science methods and tools to the data, and recognize and respond to data errors, biases, and limitations. Features: Takes an accessible, hands-on approach to handling new types of data in the social sciences Presents the key data science tools in a non-intimidating way to both social and data scientists while keeping the focus on research questions and purposes Illustrates social science and data science principles through real-world problems Links computer science concepts to practical social science research Promotes good scientific practice Provides freely available workbooks with data, code, and practical programming exercises, through Binder and GitHub New to the Second Edition: Increased use of examples from different areas of social sciences New chapter on dealing with Bias and Fairness in Machine Learning models Expanded chapters focusing on Machine Learning and Text Analysis Revamped hands-on Jupyter notebooks to reinforce concepts covered in each chapter This classroom-tested book fills a major gap in graduate- and professional-level data science and social science education. It can be used to train a new generation of social data scientists to tackle real-world problems and improve the skills and competencies of applied social scientists and public policy practitioners. It empowers you to use the massive and rapidly growing amounts of available data to interpret economic and social activities in a scientific and rigorous manner.
Errors Of Reasoning Naturalizing The Logic Of Inference
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Author : John Woods
language : en
Publisher:
Release Date : 2013-07
Errors Of Reasoning Naturalizing The Logic Of Inference written by John Woods and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07 with Philosophy categories.
Errors of Reasoning is the long-awaited continuation of the author's investigation of the logic of cognitive systems. The present focus is the individual human reasoner operating under the conditions and pressures of real life with capacities and resources the natural world makes available to him. The ensuing logic is thus agent-centred, goal-directed, and time-and-action oriented. It is also as psychologically real a logic as consistent with lawlike regularities of the better-developed empirical sciences of cognition. A point of departure for the book is that good reasoning is typically reasoning that does not meet the orthodox logician's requirements of either deductive validity or the sort of inductive strength sought for by the statistico-empirical sciences. A central objective here is to fashion a logic for this "third-way" reasoning. In so doing, substantial refinements are proposed for mainline treatments of nonmonotonic, defeasible, autoepistemic and default reasoning. A further departure from orthodox orientations is the eschewal of all idealizations short of those required for the descriptive adequacy of the relevant parts of empirical science. Also banned is any unearned assumption of a logic's normative authority to judge inferential behaviour as it actually occurs on the ground. The logic that emerges is therefore a naturalized logic, a proposed transformation of orthodox logics in the manner of the naturalization, more than forty years ago, of the traditional approaches to analytic epistemology. A byproduct of the transformation is the abandonment of justification as a general condition of knowledge, especially in third-way contexts. A test case for this new approach is an account of erroneous reasoning, including inferences usually judged fallacious, that outperforms its rivals in theoretical depth and empirical sensitivity. Errors of Reasoning is required reading in all research communities that seek a realistic understanding of human inference: Logic, formal and informal, AI and the other branches of cognitive science, argumentation theory, and theories of legal reasoning. Indeed the book is a standing challenge to all normatively idealized theories of assessable human performance. John Woods is Director of The Abductive Systems Group at the University of British Columbia, and was formerly the Charles S. Peirce Professor of Logic in the Group on Logic and Computation in the Department of Computer Science, King's College London. He is author of Paradox and Paraconsistency (2003) and with Dov Gabbay, of Agenda Relevance (2003) and The Reach of Abduction (2005). His pathbreaking The Logic of Fiction appeared in 1974, with a second edition by College Publications, 2009.
Probability Theory And Statistical Inference
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Author : Aris Spanos
language : en
Publisher: Cambridge University Press
Release Date : 2019-09-19
Probability Theory And Statistical Inference written by Aris Spanos and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-19 with Business & Economics categories.
This empirical research methods course enables informed implementation of statistical procedures, giving rise to trustworthy evidence.
Causal Inference
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Author : Scott Cunningham
language : en
Publisher: Yale University Press
Release Date : 2021-01-26
Causal Inference written by Scott Cunningham and has been published by Yale University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-26 with Business & Economics categories.
An accessible, contemporary introduction to the methods for determining cause and effect in the Social Sciences “Causation versus correlation has been the basis of arguments—economic and otherwise—since the beginning of time. Causal Inference: The Mixtape uses legit real-world examples that I found genuinely thought-provoking. It’s rare that a book prompts readers to expand their outlook; this one did for me.”—Marvin Young (Young MC) Causal inference encompasses the tools that allow social scientists to determine what causes what. In a messy world, causal inference is what helps establish the causes and effects of the actions being studied—for example, the impact (or lack thereof) of increases in the minimum wage on employment, the effects of early childhood education on incarceration later in life, or the influence on economic growth of introducing malaria nets in developing regions. Scott Cunningham introduces students and practitioners to the methods necessary to arrive at meaningful answers to the questions of causation, using a range of modeling techniques and coding instructions for both the R and the Stata programming languages.
Essentials Of Statistical Inference
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Author : G. A. Young
language : en
Publisher: Cambridge University Press
Release Date : 2005-07-25
Essentials Of Statistical Inference written by G. A. Young and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-07-25 with Mathematics categories.
Aimed at advanced undergraduates and graduate students in mathematics and related disciplines, this engaging textbook gives a concise account of the main approaches to inference, with particular emphasis on the contrasts between them. It is the first textbook to synthesize contemporary material on computational topics with basic mathematical theory.