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Foundations Of Inference In Natural Science
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Book Synopsis Foundations of Inference in Natural Science by : J O Wisdom
Download or read book Foundations of Inference in Natural Science written by J O Wisdom and published by Routledge. This book was released on 2013-04-15 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Originally published in 1952. This book is a critical survey of the views of scientific inference that have been developed since the end of World War I. It contains some detailed exposition of ideas – notably of Keynes – that were cryptically put forward, often quoted, but nowhere explained. Part I discusses and illustrates the method of hypothesis. Part II concerns induction. Part III considers aspects of the theory of probability that seem to bear on the problem of induction and Part IV outlines the shape of this problem and its solution take if transformed by the present approach.
Book Synopsis Foundations of Inference in Natural Science by : J O Wisdom
Download or read book Foundations of Inference in Natural Science written by J O Wisdom and published by Routledge. This book was released on 2013-04-15 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: Originally published in 1952. This book is a critical survey of the views of scientific inference that have been developed since the end of World War I. It contains some detailed exposition of ideas – notably of Keynes – that were cryptically put forward, often quoted, but nowhere explained. Part I discusses and illustrates the method of hypothesis. Part II concerns induction. Part III considers aspects of the theory of probability that seem to bear on the problem of induction and Part IV outlines the shape of this problem and its solution take if transformed by the present approach.
Book Synopsis Statistical Foundations, Reasoning and Inference by : Göran Kauermann
Download or read book Statistical Foundations, Reasoning and Inference written by Göran Kauermann and published by Springer Nature. This book was released on 2021-09-30 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a comprehensive introduction to statistical principles, concepts and methods that are essential in modern statistics and data science. The topics covered include likelihood-based inference, Bayesian statistics, regression, statistical tests and the quantification of uncertainty. Moreover, the book addresses statistical ideas that are useful in modern data analytics, including bootstrapping, modeling of multivariate distributions, missing data analysis, causality as well as principles of experimental design. The textbook includes sufficient material for a two-semester course and is intended for master’s students in data science, statistics and computer science with a rudimentary grasp of probability theory. It will also be useful for data science practitioners who want to strengthen their statistics skills.
Book Synopsis Foundations and Philosophy of Epistemic Applications of Probability Theory by : W.L. Harper
Download or read book Foundations and Philosophy of Epistemic Applications of Probability Theory written by W.L. Harper and published by Springer Science & Business Media. This book was released on 1976 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proceedings of an International Research Colloquium held at the University of Western Ontario, 10-13 May 1973.
Book Synopsis The Logical Foundations of Statistical Inference by : Henry E. Kyburg Jr.
Download or read book The Logical Foundations of Statistical Inference written by Henry E. Kyburg Jr. and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Everyone knows it is easy to lie with statistics. It is important then to be able to tell a statistical lie from a valid statistical inference. It is a relatively widely accepted commonplace that our scientific knowledge is not certain and incorrigible, but merely probable, subject to refinement, modifi cation, and even overthrow. The rankest beginner at a gambling table understands that his decisions must be based on mathematical ex pectations - that is, on utilities weighted by probabilities. It is widely held that the same principles apply almost all the time in the game of life. If we turn to philosophers, or to mathematical statisticians, or to probability theorists for criteria of validity in statistical inference, for the general principles that distinguish well grounded from ill grounded generalizations and laws, or for the interpretation of that probability we must, like the gambler, take as our guide in life, we find disagreement, confusion, and frustration. We might be prepared to find disagreements on a philosophical and theoretical level (although we do not find them in the case of deductive logic) but we do not expect, and we may be surprised to find, that these theoretical disagreements lead to differences in the conclusions that are regarded as 'acceptable' in the practice of science and public affairs, and in the conduct of business.
Book Synopsis Statistical Inference as Severe Testing by : Deborah G. Mayo
Download or read book Statistical Inference as Severe Testing written by Deborah G. Mayo and published by Cambridge University Press. This book was released on 2018-09-20 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.
Book Synopsis Foundations of Statistical Natural Language Processing by : Christopher Manning
Download or read book Foundations of Statistical Natural Language Processing written by Christopher Manning and published by MIT Press. This book was released on 1999-05-28 with total page 719 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.
Book Synopsis Model Based Inference in the Life Sciences by : David R. Anderson
Download or read book Model Based Inference in the Life Sciences written by David R. Anderson and published by Springer Science & Business Media. This book was released on 2007-12-22 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook introduces a science philosophy called "information theoretic" based on Kullback-Leibler information theory. It focuses on a science philosophy based on "multiple working hypotheses" and statistical models to represent them. The text is written for people new to the information-theoretic approaches to statistical inference, whether graduate students, post-docs, or professionals. Readers are however expected to have a background in general statistical principles, regression analysis, and some exposure to likelihood methods. This is not an elementary text as it assumes reasonable competence in modeling and parameter estimation.
Book Synopsis The Nature of Scientific Evidence by : Mark L. Taper
Download or read book The Nature of Scientific Evidence written by Mark L. Taper and published by . This book was released on 2004-10 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mark Taper, Subhash Lele and an esteemed group of contributors explore the relationships among hypotheses, models, data and interference on which scientific progress rests in an attempt to develop a new quantitative framework for evidence.
Book Synopsis Foundations of Inference in Natural Science by : John Dulton Wisdom
Download or read book Foundations of Inference in Natural Science written by John Dulton Wisdom and published by . This book was released on 1952 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Yorick's World written by Peter Caws and published by Univ of California Press. This book was released on 2023-04-28 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: Peter Caws provides a fresh and often iconoclastic treatment of some of the most vexing problems in the philosophy of science: explanation, induction, causality, evolution, discovery, artificial intelligence, and the social implications of technological rationality. Caws's work has been shaped equally by the insights of Continental philosophy and a concern with scientific practice. In these twenty-eight essays spanning more than a quarter of a century, he ranges from discussions of the work of French philosopher Gaston Bachelard, to relations between science and surrealism, to the concept of intentionality, to the limits of quantitative description. A lively mix of history, theory, speculation, and analysis, Yorick's World presents a vision of science that includes human history and social life. It will interest professional philosophers and scientists, and at the same time its directness will make it readily accessible to nontechnical readers.
Book Synopsis Foundations of Info-metrics by : Amos Golan
Download or read book Foundations of Info-metrics written by Amos Golan and published by Oxford University Press. This book was released on 2018 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: Info-metrics is the science of modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information. It is at the intersection of information theory, statistical inference, and decision-making under uncertainty. It plays an important role in helping make informed decisions even when there is inadequate or incomplete information because it provides a framework to process available information with minimal reliance on assumptions that cannot be validated. In this pioneering book, Amos Golan, a leader in info-metrics, focuses on unifying information processing, modeling and inference within a single constrained optimization framework. Foundations of Info-Metrics provides an overview of modeling and inference, rather than a problem specific model, and progresses from the simple premise that information is often insufficient to provide a unique answer for decisions we wish to make. Each decision, or solution, is derived from the available input information along with a choice of inferential procedure. The book contains numerous multidisciplinary applications and case studies, which demonstrate the simplicity and generality of the framework in real world settings. Examples include initial diagnosis at an emergency room, optimal dose decisions, election forecasting, network and information aggregation, weather pattern analyses, portfolio allocation, strategy inference for interacting entities, incorporation of prior information, option pricing, and modeling an interacting social system. Graphical representations illustrate how results can be visualized while exercises and problem sets facilitate extensions. This book is this designed to be accessible for researchers, graduate students, and practitioners across the disciplines.
Book Synopsis Statistical Foundations of Data Science by : Jianqing Fan
Download or read book Statistical Foundations of Data Science written by Jianqing Fan and published by CRC Press. This book was released on 2020-09-21 with total page 942 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications. The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.
Book Synopsis Metaphysical Foundations of Natural Science by : Immanuel Kant
Download or read book Metaphysical Foundations of Natural Science written by Immanuel Kant and published by Cambridge University Press. This book was released on 2004 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: Preface 1. Metaphysical foundations of phoronomy 2. Metaphysical foundations of dynamics 3. Metaphysical foundations of mechanics 4. Metaphysical foundations of phenomenology.
Book Synopsis Statistical Models and Causal Inference by : David A. Freedman
Download or read book Statistical Models and Causal Inference written by David A. Freedman and published by Cambridge University Press. This book was released on 2010 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: David A. Freedman presents a definitive synthesis of his approach to statistical modeling and causal inference in the social sciences.
Book Synopsis Probability is the Very Guide of Life by : Henry Ely Kyburg
Download or read book Probability is the Very Guide of Life written by Henry Ely Kyburg and published by Open Court Publishing. This book was released on 2003 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection of philosophical essays looks at various technical problems in the use of probability theory for guidance in practical decisions. This text is intended for those who already have a basic grounding in philosophy, logic and probabilty theory.
Book Synopsis Causal Inference in Statistics, Social, and Biomedical Sciences by : Guido W. Imbens
Download or read book Causal Inference in Statistics, Social, and Biomedical Sciences written by Guido W. Imbens and published by Cambridge University Press. This book was released on 2015-04-06 with total page 647 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.
