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Author: Daniel Kahneman
Publisher: Cambridge University Press
ISBN: 9780521284141
Category : Psychology
Languages : en
Pages : 574
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Book Description
Thirty-five chapters describe various judgmental heuristics and the biases they produce, not only in laboratory experiments, but in important social, medical, and political situations as well. Most review multiple studies or entire subareas rather than describing single experimental studies.
Author: Daniel Kahneman
Publisher: Cambridge University Press
ISBN: 9780521284141
Category : Psychology
Languages : en
Pages : 574
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Book Description
Thirty-five chapters describe various judgmental heuristics and the biases they produce, not only in laboratory experiments, but in important social, medical, and political situations as well. Most review multiple studies or entire subareas rather than describing single experimental studies.
Author: National Research Council
Publisher: National Academies Press
ISBN: 030904894X
Category : Science
Languages : en
Pages : 668
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Book Description
The public depends on competent risk assessment from the federal government and the scientific community to grapple with the threat of pollution. When risk reports turn out to be overblownâ€"or when risks are overlookedâ€"public skepticism abounds. This comprehensive and readable book explores how the U.S. Environmental Protection Agency (EPA) can improve its risk assessment practices, with a focus on implementation of the 1990 Clean Air Act Amendments. With a wealth of detailed information, pertinent examples, and revealing analysis, the volume explores the "default option" and other basic concepts. It offers two views of EPA operations: The first examines how EPA currently assesses exposure to hazardous air pollutants, evaluates the toxicity of a substance, and characterizes the risk to the public. The second, more holistic, view explores how EPA can improve in several critical areas of risk assessment by focusing on cross-cutting themes and incorporating more scientific judgment. This comprehensive volume will be important to the EPA and other agencies, risk managers, environmental advocates, scientists, faculty, students, and concerned individuals.
Author: Timothy L. Lash
Publisher: Springer Science & Business Media
ISBN: 0387879595
Category : Medical
Languages : en
Pages : 200
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Book Description
Bias analysis quantifies the influence of systematic error on an epidemiology study’s estimate of association. The fundamental methods of bias analysis in epi- miology have been well described for decades, yet are seldom applied in published presentations of epidemiologic research. More recent advances in bias analysis, such as probabilistic bias analysis, appear even more rarely. We suspect that there are both supply-side and demand-side explanations for the scarcity of bias analysis. On the demand side, journal reviewers and editors seldom request that authors address systematic error aside from listing them as limitations of their particular study. This listing is often accompanied by explanations for why the limitations should not pose much concern. On the supply side, methods for bias analysis receive little attention in most epidemiology curriculums, are often scattered throughout textbooks or absent from them altogether, and cannot be implemented easily using standard statistical computing software. Our objective in this text is to reduce these supply-side barriers, with the hope that demand for quantitative bias analysis will follow.
Author: David G. Taylor
Publisher:
ISBN:
Category : Chemicals
Languages : en
Pages : 1290
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Book Description
Author: Thomas Gilovich
Publisher: Cambridge University Press
ISBN: 9780521796798
Category : Education
Languages : en
Pages : 884
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Book Description
This book, first published in 2002, compiles psychologists' best attempts to answer important questions about intuitive judgment.
Author: Camille Morvan
Publisher: CRC Press
ISBN: 1351350609
Category : Business & Economics
Languages : en
Pages : 93
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Book Description
Amos Tversky and Daniel Kahneman’s 1974 paper ‘Judgement Under Uncertainty: Heuristics and Biases’ is a landmark in the history of psychology. Though a mere seven pages long, it has helped reshape the study of human rationality, and had a particular impact on economics – where Tversky and Kahneman’s work helped shape the entirely new sub discipline of ‘behavioral economics.’ The paper investigates human decision-making, specifically what human brains tend to do when we are forced to deal with uncertainty or complexity. Based on experiments carried out with volunteers, Tversky and Kahneman discovered that humans make predictable errors of judgement when forced to deal with ambiguous evidence or make challenging decisions. These errors stem from ‘heuristics’ and ‘biases’ – mental shortcuts and assumptions that allow us to make swift, automatic decisions, often usefully and correctly, but occasionally to our detriment. The paper’s huge influence is due in no small part to its masterful use of high-level interpretative and analytical skills – expressed in Tversky and Kahneman’s concise and clear definitions of the basic heuristics and biases they discovered. Still providing the foundations of new work in the field 40 years later, the two psychologists’ definitions are a model of how good interpretation underpins incisive critical thinking.
Author: Eurachem/CITAC Working Group
Publisher:
ISBN: 9780948926150
Category : Chemistry, Analytic
Languages : en
Pages : 120
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Book Description
Author: Paul De Bièvre
Publisher: Springer Science & Business Media
ISBN: 3662051737
Category : Science
Languages : en
Pages : 294
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Book Description
It is now becoming recognized in the measurement community that it is as important to communicate the uncertainty related to a specific measurement as it is to report the measurement itself. Without knowing the uncertainty, it is impossible for the users of the result to know what confidence can be placed in it; it is also impossible to assess the comparability of different measurements of the same parameter. This volume collects 20 outstanding papers on the topic, mostly published from 1999-2002 in the journal "Accreditation and Quality Assurance." They provide the rationale for why it is important to evaluate and report the uncertainty of a result in a consistent manner. They also describe the concept of uncertainty, the methodology for evaluating uncertainty, and the advantages of using suitable reference materials. Finally, the benefits to both the analytical laboratory and the user of the results are considered.
Author: Leonardo Calderon
Publisher: BoD – Books on Demand
ISBN: 9535108131
Category : Science
Languages : en
Pages : 442
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Book Description
Nowadays, Chromatography is the most versatile and widespread technique employed in modern chemical analysis and plays a vital role in the advancement of chemistry, biology, medicine and related fields of research. Because of the inherent simplicity and ease of operation, it can be used together with a wide range of detection systems, including electrochemical, photometric and mass spectrometry, being an invaluable laboratory tool for the separation and identification of compounds. The purpose of this book is not only to present the latest state and development tendencies of chromatography, but to bring the reader useful information on separation sciences to enable him to use chromatography on his research field. Taking into account the large amount of knowledge about chromatography theory and practice presented in the book, it has three major parts: applications, theory and sample preparation. The book is also intended for both graduate and postgraduate students in fields such as chemistry, biology, biotechnology, forensic, medicine, pharmacology and engineering, and as a reference for professionals and practitioners.
Author: Luis Tenorio
Publisher: SIAM
ISBN: 1611974917
Category : Mathematics
Languages : en
Pages : 275
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Book Description
Inverse problems are found in many applications, such as medical imaging, engineering, astronomy, and geophysics, among others. To solve an inverse problem is to recover an object from noisy, usually indirect observations. Solutions to inverse problems are subject to many potential sources of error introduced by approximate mathematical models, regularization methods, numerical approximations for efficient computations, noisy data, and limitations in the number of observations; thus it is important to include an assessment of the uncertainties as part of the solution. Such assessment is interdisciplinary by nature, as it requires, in addition to knowledge of the particular application, methods from applied mathematics, probability, and statistics. This book bridges applied mathematics and statistics by providing a basic introduction to probability and statistics for uncertainty quantification in the context of inverse problems, as well as an introduction to statistical regularization of inverse problems. The author covers basic statistical inference, introduces the framework of ill-posed inverse problems, and explains statistical questions that arise in their applications. An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems?includes many examples that explain techniques which are useful to address general problems arising in uncertainty quantification, Bayesian and non-Bayesian statistical methods and discussions of their complementary roles, and analysis of a real data set to illustrate the methodology covered throughout the book.
