Assessment of error and uncertainty is a vital component of both natural and social science. This edited volume presents case studies of research practices across a wide spectrum of scientific fields. It compares methodologies and presents the ingredients needed for an overarching framework applicable to all.
Assessment of error and uncertainty is a vital component of both natural and social science. This edited volume presents case studies of research practices across a wide spectrum of scientific fields. It compares methodologies and presents the ingredients needed for an overarching framework applicable to all.
"Body Physics was designed to meet the objectives of a one-term high school or freshman level course in physical science, typically designed to provide non-science majors and undeclared students with exposure to the most basic principles in physics while fulfilling a science-with-lab core requirement. The content level is aimed at students taking their first college science course, whether or not they are planning to major in science. However, with minor supplementation by other resources, such as OpenStax College Physics, this textbook could easily be used as the primary resource in 200-level introductory courses. Chapters that may be more appropriate for physics courses than for general science courses are noted with an asterisk symbol (*). Of course this textbook could be used to supplement other primary resources in any physics course covering mechanics and thermodynamics"--Textbook Web page.
All measurements are subject to error because no quantity can be known exactly; hence, any measurement has a probability of lying within a certain range. The more precise the measurement, the smaller the range of uncertainty. Uncertainty, Calibration and Probability is a comprehensive treatment of the statistics and methods of estimating these calibration uncertainties. The book features the general theory of uncertainty involving the combination (convolution) of non-Gaussian, student t, and Gaussian distributions; the use of rectangular distributions to represent systematic uncertainties; and measurable and nonmeasurable uncertainties that require estimation. The author also discusses sources of measurement errors and curve fitting with numerous examples of uncertainty case studies. Many useful tables and computational formulae are included as well. All formulations are discussed and demonstrated with the minimum of mathematical knowledge assumed. This second edition offers additional examples in each chapter, and detailed additions and alterations made to the text. New chapters consist of the general theory of uncertainty and applications to industry and a new section discusses the use of orthogonal polynomials in curve fitting. Focusing on practical problems of measurement, Uncertainty, Calibration and Probability is an invaluable reference tool for R&D laboratories in the engineering/manufacturing industries and for undergraduate and graduate students in physics, engineering, and metrology.
One of the pathways by which the scientific community confirms the validity of a new scientific discovery is by repeating the research that produced it. When a scientific effort fails to independently confirm the computations or results of a previous study, some fear that it may be a symptom of a lack of rigor in science, while others argue that such an observed inconsistency can be an important precursor to new discovery. Concerns about reproducibility and replicability have been expressed in both scientific and popular media. As these concerns came to light, Congress requested that the National Academies of Sciences, Engineering, and Medicine conduct a study to assess the extent of issues related to reproducibility and replicability and to offer recommendations for improving rigor and transparency in scientific research. Reproducibility and Replicability in Science defines reproducibility and replicability and examines the factors that may lead to non-reproducibility and non-replicability in research. Unlike the typical expectation of reproducibility between two computations, expectations about replicability are more nuanced, and in some cases a lack of replicability can aid the process of scientific discovery. This report provides recommendations to researchers, academic institutions, journals, and funders on steps they can take to improve reproducibility and replicability in science.
“Evaluating Measurement Accuracy, 2nd Edition” is intended for those who are concerned with measurements in any field of science or technology. It reflects the latest developments in metrology and offers new results, but is designed to be accessible to readers at different levels: scientists who advance the field of metrology, engineers and experimental scientists who use measurements as tool in their professions, students and graduate students in natural sciences and engineering, and, in parts describing practical recommendations, technicians performing mass measurements in industry, quality control, and trade. This book presents material from the practical perspective and offers solutions and recommendations for problems that arise in conducting real-life measurements. This new edition adds a method for estimating accuracy of indirect measurements with independent arguments, whose development Dr. Rabinovich was able to complete very recently. This method, which is called the Method of Enumeration, produces estimates that are no longer approximate, similar to the way the method of reduction described in the first edition removed approximation in estimating uncertainty of indirect measurements with dependent arguments. The method of enumeration completes addressing the range of problems whose solutions signify the emergence of the new theory of accuracy of measurements. A new method is added for building a composition of histograms, and this method forms a theoretical basis for the method of enumeration.Additionally, as a companion to this book, a concise practical guide that assembles simple step-by-step procedures for typical tasks the practitioners are likely to encounter in measurement accuracy estimation is available at SpringerLink.
Computer simulation has become an important means for obtaining knowledge about nature. The practice of scientific simulation and the frequent use of uncertain simulation results in public policy raise a wide range of philosophical questions. Most prominently highlighted is the field of anthropogenic climate change-are humans currently changing the
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.