Quantifying Measurement
Quantifying Measurement

Author: Jeffrey H Williams

Publisher: Morgan & Claypool Publishers

Published: 2016-11-01

Total Pages: 169

ISBN-13: 1681744341

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Measurements and experiments are made each and every day, in fields as disparate as particle physics, chemistry, economics and medicine, but have you ever wondered why it is that a particular experiment has been designed to be the way it is. Indeed, how do you design an experiment to measure something whose value is unknown, and what should your considerations be on deciding whether an experiment has yielded the sought after, or indeed any useful result? These are old questions, and they are the reason behind this volume. We will explore the origins of the methods of data analysis that are today routinely applied to all measurements, but which were unknown before the mid-19th Century. Anyone who is interested in the relationship between the precision and accuracy of measurements will find this volume useful. Whether you are a physicist, a chemist, a social scientist, or a student studying one of these subjects, you will discover that the basis of measurement is the struggle to identify the needle of useful data hidden in the haystack of obscuring background noise.

Astrophysics For Dummies
Astrophysics For Dummies

Author: Cynthia Phillips

Publisher: John Wiley & Sons

Published: 2024-02-23

Total Pages: 415

ISBN-13: 1394235054

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Discover the undiscovered with this jargon-free introduction to astrophysics Astronomy is the study of what you see in the sky. Physics is the study of how things work. Astrophysics is the study of how things in the sky work, from large objects to tiny particles. Astrophysics For Dummies breaks it all down for you, making this difficult but fascinating topic accessible to anyone. Tracking the topics covered in a typical undergraduate astrophysics class, this book will teach you the essential pieces to understanding our universe. Get ready to launch into outer space with this ever-changing branch of science. Discover the latest advances in the world of astrophysics Understand how and why galaxies form and evolve Find out the origins of cosmic rays Get a standalone primer on the science or supplement your astrophysics course Students in introductory astrophysics courses and would-be astronomy buffs who want to better understand the mechanics of the universe will love Astrophysics For Dummies.

Quantifying Uncertainty in Subsurface Systems
Quantifying Uncertainty in Subsurface Systems

Author: Céline Scheidt

Publisher: John Wiley & Sons

Published: 2018-04-27

Total Pages: 304

ISBN-13: 1119325870

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Under the Earth’s surface is a rich array of geological resources, many with potential use to humankind. However, extracting and harnessing them comes with enormous uncertainties, high costs, and considerable risks. The valuation of subsurface resources involves assessing discordant factors to produce a decision model that is functional and sustainable. This volume provides real-world examples relating to oilfields, geothermal systems, contaminated sites, and aquifer recharge. Volume highlights include: • A multi-disciplinary treatment of uncertainty quantification • Case studies with actual data that will appeal to methodology developers • A Bayesian evidential learning framework that reduces computation and modeling time Quantifying Uncertainty in Subsurface Systems is a multidisciplinary volume that brings together five major fields: information science, decision science, geosciences, data science and computer science. It will appeal to both students and practitioners, and be a valuable resource for geoscientists, engineers and applied mathematicians. Read the Editors’ Vox: https://eos.org/editors-vox/quantifying-uncertainty-about-earths-resources

Quantifying the Unknown
Quantifying the Unknown

Author: Steinar Løve Ellefmo

Publisher:

Published: 2019

Total Pages: 138

ISBN-13: 9788202591045

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Copper, zinc, gold and silver mineralizations exist on the deep ocean floor, at great depths, on the Mid-Atlantic Ridge between Jan Mayen and Spitsbergen. None of these mineralizations within Norwegian jurisdiction have been thoroughly investigated yet, but they are likely to contain significant amounts of minerals and metals crucial to society and the 'Green Shift'. Should these mineralizations, which contain minerals and metals that you and I use every day, be developed and mined? The question is premature: we need to know more before we can answer it. We need to know more about the formation, location and characteristics of these potential deposits, as well as the environmental, social and financial consequences of potential extraction. We need to evaluate mining alternatives and how to process the extracted ore. How should we answer this question? The ultimate decisions will be determined politically, and knowledge will be the defining factor. Knowledge gained from proper mineral resource management. Quantifying the Unknown sets out to estimate the amount of minerals and metals on the deep ocean floor along the Mid-Atlantic Ridge, in particular, copper, zinc, gold and silver contained in so-called 'seafloor massive sulphide deposits'. These deposits are modern analogues of those mined worldwide on land today. The method used to quantify the amounts of these resources is known as 'play analysis'. It shares aspects of methodologies used on land for similar purposes and has been employed extensively to assess untapped petroleum resources on the Norwegian Continental Shelf. Play analysis enables a quantification of the potential as well as associated uncertainty. The potential is large, but the uncertainty is also significant. Whether and how this potential is realized remains to be seen.

Quantifying and Understanding Plant Nitrogen Uptake for Systems Modeling
Quantifying and Understanding Plant Nitrogen Uptake for Systems Modeling

Author: Liwang Ma

Publisher: CRC Press

Published: 2008-08-27

Total Pages: 326

ISBN-13: 1420052977

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Discusses New Advancements to Improve Existing Simulations of Plant NitrogenWritten by research pioneers and leading scientists in the area of agricultural systems, Quantifying and Understanding Plant Nitrogen Uptake for Systems Modeling comprehensively covers plant N uptake in agricultural system models, especially for building soil-plant system m

Quantifying Systemic Risk
Quantifying Systemic Risk

Author: Joseph G. Haubrich

Publisher: University of Chicago Press

Published: 2013-01-24

Total Pages: 286

ISBN-13: 0226319288

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In the aftermath of the recent financial crisis, the federal government has pursued significant regulatory reforms, including proposals to measure and monitor systemic risk. However, there is much debate about how this might be accomplished quantitatively and objectively—or whether this is even possible. A key issue is determining the appropriate trade-offs between risk and reward from a policy and social welfare perspective given the potential negative impact of crises. One of the first books to address the challenges of measuring statistical risk from a system-wide persepective, Quantifying Systemic Risk looks at the means of measuring systemic risk and explores alternative approaches. Among the topics discussed are the challenges of tying regulations to specific quantitative measures, the effects of learning and adaptation on the evolution of the market, and the distinction between the shocks that start a crisis and the mechanisms that enable it to grow.

Applying Quantitative Bias Analysis to Epidemiologic Data
Applying Quantitative Bias Analysis to Epidemiologic Data

Author: Timothy L. Lash

Publisher: Springer Science & Business Media

Published: 2011-04-14

Total Pages: 200

ISBN-13: 0387879595

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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.

Learning to Quantify
Learning to Quantify

Author: Andrea Esuli

Publisher: Springer Nature

Published: 2023-04-17

Total Pages: 145

ISBN-13: 3031204670

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This open access book provides an introduction and an overview of learning to quantify (a.k.a. “quantification”), i.e. the task of training estimators of class proportions in unlabeled data by means of supervised learning. In data science, learning to quantify is a task of its own related to classification yet different from it, since estimating class proportions by simply classifying all data and counting the labels assigned by the classifier is known to often return inaccurate (“biased”) class proportion estimates. The book introduces learning to quantify by looking at the supervised learning methods that can be used to perform it, at the evaluation measures and evaluation protocols that should be used for evaluating the quality of the returned predictions, at the numerous fields of human activity in which the use of quantification techniques may provide improved results with respect to the naive use of classification techniques, and at advanced topics in quantification research. The book is suitable to researchers, data scientists, or PhD students, who want to come up to speed with the state of the art in learning to quantify, but also to researchers wishing to apply data science technologies to fields of human activity (e.g., the social sciences, political science, epidemiology, market research) which focus on aggregate (“macro”) data rather than on individual (“micro”) data.

An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems
An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems

Author: Luis Tenorio

Publisher: SIAM

Published: 2017-07-06

Total Pages: 275

ISBN-13: 1611974917

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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.

Quantifying the User Experience
Quantifying the User Experience

Author: Jeff Sauro

Publisher: Morgan Kaufmann

Published: 2016-07-12

Total Pages: 374

ISBN-13: 0128025484

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Quantifying the User Experience: Practical Statistics for User Research, Second Edition, provides practitioners and researchers with the information they need to confidently quantify, qualify, and justify their data. The book presents a practical guide on how to use statistics to solve common quantitative problems that arise in user research. It addresses questions users face every day, including, Is the current product more usable than our competition? Can we be sure at least 70% of users can complete the task on their first attempt? How long will it take users to purchase products on the website? This book provides a foundation for statistical theories and the best practices needed to apply them. The authors draw on decades of statistical literature from human factors, industrial engineering, and psychology, as well as their own published research, providing both concrete solutions (Excel formulas and links to their own web-calculators), along with an engaging discussion on the statistical reasons why tests work and how to effectively communicate results. Throughout this new edition, users will find updates on standardized usability questionnaires, a new chapter on general linear modeling (correlation, regression, and analysis of variance), with updated examples and case studies throughout. - Completely updated to provide practical guidance on solving usability testing problems with statistics for any project, including those using Six Sigma practices - Includes new and revised information on standardized usability questionnaires - Includes a completely new chapter introducing correlation, regression, and analysis of variance - Shows practitioners which test to use, why they work, and best practices for application, along with easy-to-use Excel formulas and web-calculators for analyzing data - Recommends ways for researchers and practitioners to communicate results to stakeholders in plain English