Information Inference And Decision
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Information Inference And Decision
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Author : G. Menges
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Information Inference And Decision written by G. Menges 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 2012-12-06 with Social Science categories.
Under the title 'Information, Inference and Decision' this volume in the Theory and Decision Library presents some papers on issues from the borderland of statistical inference philosophy and epistemology, written by statisticians and decision theorists who belonged or are allied to the former Saarbriicken school of statistical decision theory. In the first part I make an attempt to outline an objective theory of inductive behaviour, on the basis of R. A. Fisher's statistical inference philosophy, on the one hand, and R. Carnap's inductive logic, on the other. A special problem arising in the context of the new theory, viz., the problem of vagueness of concepts (in particular in the social sciences) is treated separately by H. Skala and myself. B. Leiner has contributed some biographical and bibliographical notes on the objective theory of inductive behaviour. Part II is concerned with inference philosophy. D. A. S. Fraser, the founder of structural inference theory, characterizes and compares some inference philosophies, and discusses his own and the arguments of the critics of his structural theory. In my opinion, Fraser's structural infer ence theory is suited to complete Fisher's inference philosophy in some essential points, if not to replace it. An interesting task for future re search work is to establish the connection between Fraser's theory and Carnap's ideas in the framework of an objective theory of inductive behaviour.
On Science Inference Information And Decision Making
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Author : A. Szaniawski
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
On Science Inference Information And Decision Making written by A. Szaniawski 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 2012-12-06 with Philosophy categories.
There are two competing pictures of science. One considers science as a system of inferences, whereas another looks at science as a system of actions. The essays included in this collection offer a view which intends to combine both pictures. This compromise is well illustrated by Szaniawski's analysis of statistical inferences. It is shown that traditional approaches to the foundations of statistics do not need to be regarded as conflicting with each other. Thus, statistical rules can be treated as rules of behaviour as well as rules of inference. Szaniawski's uniform approach relies on the concept of rationality, analyzed from the point of view of decision theory. Applications of formal tools to the problem of justice and division of goods shows that the concept of rationality has a wider significance. Audience: The book will be of interest to philosophers of science, logicians, ethicists and mathematicians.
Inference And Decision Making With Heterogeneous Information
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Author : Jingqi Yu
language : en
Publisher:
Release Date : 2021
Inference And Decision Making With Heterogeneous Information written by Jingqi Yu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Consumer behavior categories.
Every day, people are bombarded with information from various sources, and yet they do not have nearly enough time to process it. How do people sift through information and decide what to use, and what do they rely on to make these decisions? How do people respond to inconsistent or conflicting information? The goal of this dissertation is to investigate these core questions as well as their implications in education and business. To do this, my work takes a highly interdisciplinary approach that combines cognitive science, consumer behavior, information systems, and communication studies, using a blend of behavioral experimentation and computational cognitive modeling. I present three papers that examine the mechanisms people engage in when they integrate information displayed in different forms and from different sources in educational and consumer contexts. The first paper approaches learning statistical inference in an experientially grounded way by developing computer simulations. It reveals people's flexibility to "game" the game, highlighting the importance of ensuring alignment between visual training and learning objectives in educational games. The second paper uses a computational approach to systematically reveal the common ways people ascribe meanings to the five-star rating system when shopping online. The findings suggest two ways to improve the interactions between reputation and feedback systems and their users: normalizing ratings with commentaries and normalizing ratings with clarification and education. The third paper demonstrates how people integrate ratings and reviews into their purchase decisions, and how these decisions can be influenced by the consumers' justifications. It also unveils the role of information relevance and similarity in social cognition. These insights could be leveraged by different players in the market to influence consumer choice. By examining information integration in education and digital economy, this dissertation helps create a more comprehensive picture of how people generate, disseminate, and consume information. It highlights the mechanisms by which people integrate heterogeneous information to make inferences and decisions, as well as cues and heuristics they rely on to facilitate these everyday tasks. This expanded understanding informs the development of systems whose goal is to facilitate user navigation in the era of big data.
Inference And Decision
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Author : Günter Menges
language : en
Publisher: University Press of Canada ; Delhi : Hindustan Publishing Corporation
Release Date : 1973
Inference And Decision written by Günter Menges and has been published by University Press of Canada ; Delhi : Hindustan Publishing Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 1973 with Business & Economics categories.
The Effects Of Information Load On Inferences In Decision Making In A Decision Support System Environment
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Author : Russell K. H. Ching
language : en
Publisher:
Release Date : 1994
The Effects Of Information Load On Inferences In Decision Making In A Decision Support System Environment written by Russell K. H. Ching and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Decision making categories.
An Introduction To Bayesian Inference And Decision
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Author : Robert L. Winkler
language : en
Publisher: Holt McDougal
Release Date : 1972
An Introduction To Bayesian Inference And Decision written by Robert L. Winkler and has been published by Holt McDougal this book supported file pdf, txt, epub, kindle and other format this book has been release on 1972 with Mathematics categories.
Advances In Info Metrics
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Author : Min Chen
language : en
Publisher: Oxford University Press
Release Date : 2020-11-06
Advances In Info Metrics written by Min Chen 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 2020-11-06 with Business & Economics categories.
Info-metrics is a framework for modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information. It is an interdisciplinary framework situated at the intersection of information theory, statistical inference, and decision-making under uncertainty. In Advances in Info-Metrics, Min Chen, J. Michael Dunn, Amos Golan, and Aman Ullah bring together a group of thirty experts to expand the study of info-metrics across the sciences and demonstrate how to solve problems using this interdisciplinary framework. Building on the theoretical underpinnings of info-metrics, the volume sheds new light on statistical inference, information, and general problem solving. The book explores the basis of information-theoretic inference and its mathematical and philosophical foundations. It emphasizes the interrelationship between information and inference and includes explanations of model building, theory creation, estimation, prediction, and decision making. Each of the nineteen chapters provides the necessary tools for using the info-metrics framework to solve a problem. The collection covers recent developments in the field, as well as many new cross-disciplinary case studies and examples. Designed to be accessible for researchers, graduate students, and practitioners across disciplines, this book provides a clear, hands-on experience for readers interested in solving problems when presented with incomplete and imperfect information.
Information Gap Decision Theory
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Author : Yakov Ben-Haim
language : en
Publisher:
Release Date : 2001
Information Gap Decision Theory written by Yakov Ben-Haim and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Business & Economics categories.
Information-Gap Decision Theory presents a distinctive new theory of decision-making under severe uncertainty. Applications in engineering design and analysis, project management, economics, strategic planning, social decision making, environmental management, medical decisions, search and evasion problems, risk assessment, and other areas are discussed. Info-gap theory deals with many of the problems and questions of classical decision analysis such as risk assessment, gambling, value of information, trade-off analysis, and preference reversal, but the distinctive character of info-gap uncertainty repeatedly gives rise to new insights and unique decision algorithms. Furthermore, this book deals with many of the difficult interface issues facing the responsible decision maker such as value judgments concerning risk and immunity to failure, as well as philosophical implications of decision under uncertainty. This book is a fresh approach to the age-old problem of deciding responsibly with deficient information. An info-gap is the disparity between what is known and what needs to be known in order to make a well-founded decision. The book begins with a discussion of info-gap models of uncertainty, which provides an innovative approach to the quantification of severe lack of information. This book can be used in advanced undergraduate and graduate courses on decision theory and risk analysis. It is also of interest to practicing decision analysts and to researchers in decision theory and in human decision-making.
Decision Making And Inference Under Limited Information And High Dimensionality
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Author : Stefano Ermon
language : en
Publisher:
Release Date : 2015
Decision Making And Inference Under Limited Information And High Dimensionality written by Stefano Ermon and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
Statistical inference in high-dimensional probabilistic models is one of the central problems of statistical machine learning and stochastic decision making. To date, only a handful of distinct methods have been developed, most notably (Markov Chain Monte Carlo) sampling, decomposition, and variational methods. In this dissertation, we will introduce a fundamentally new approach based on random projections and combinatorial optimization. Our approach provides provable guarantees on accuracy, and outperforms traditional methods in a range of domains, in particular those involving combinations of probabilistic and causal dependencies (such as those coming from physical laws) among the variables. This allows for a tighter integration between inductive and deductive reasoning, and offers a range of new modeling opportunities. As an example, we will discuss an application in the emerging field of Computational Sustainability aimed at discovering new fuel-cell materials where we greatly improved the quality of the results by incorporating prior background knowledge of the physics of the system into the model.
Introduction To Statistical Decision Theory
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Author : Silvia Bacci
language : en
Publisher: CRC Press
Release Date : 2019-07-11
Introduction To Statistical Decision Theory written by Silvia Bacci and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-11 with Mathematics categories.
Introduction to Statistical Decision Theory: Utility Theory and Causal Analysis provides the theoretical background to approach decision theory from a statistical perspective. It covers both traditional approaches, in terms of value theory and expected utility theory, and recent developments, in terms of causal inference. The book is specifically designed to appeal to students and researchers that intend to acquire a knowledge of statistical science based on decision theory. Features Covers approaches for making decisions under certainty, risk, and uncertainty Illustrates expected utility theory and its extensions Describes approaches to elicit the utility function Reviews classical and Bayesian approaches to statistical inference based on decision theory Discusses the role of causal analysis in statistical decision theory