Download or read book Quantification written by and published by Ardent Media. This book was released on with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Quantification in Science written by M. Melarango and published by CRC Press. This book was released on 1991-07-01 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume promotes order within the confusion of the many systems of units in existence. After establishing a clearer picture of science today, it examines the articulated language science by defining the units and their systems, and by offering a quick method to convert from one unit to another. Concise and to the point, it allows the reader to go from generalities to specifics-and vice versa-in a matter of minutes.
Download or read book Uncertainty Quantification and Predictive Computational Science written by Ryan G. McClarren and published by Springer. This book was released on 2018-11-23 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook teaches the essential background and skills for understanding and quantifying uncertainties in a computational simulation, and for predicting the behavior of a system under those uncertainties. It addresses a critical knowledge gap in the widespread adoption of simulation in high-consequence decision-making throughout the engineering and physical sciences. Constructing sophisticated techniques for prediction from basic building blocks, the book first reviews the fundamentals that underpin later topics of the book including probability, sampling, and Bayesian statistics. Part II focuses on applying Local Sensitivity Analysis to apportion uncertainty in the model outputs to sources of uncertainty in its inputs. Part III demonstrates techniques for quantifying the impact of parametric uncertainties on a problem, specifically how input uncertainties affect outputs. The final section covers techniques for applying uncertainty quantification to make predictions under uncertainty, including treatment of epistemic uncertainties. It presents the theory and practice of predicting the behavior of a system based on the aggregation of data from simulation, theory, and experiment. The text focuses on simulations based on the solution of systems of partial differential equations and includes in-depth coverage of Monte Carlo methods, basic design of computer experiments, as well as regularized statistical techniques. Code references, in python, appear throughout the text and online as executable code, enabling readers to perform the analysis under discussion. Worked examples from realistic, model problems help readers understand the mechanics of applying the methods. Each chapter ends with several assignable problems. Uncertainty Quantification and Predictive Computational Science fills the growing need for a classroom text for senior undergraduate and early-career graduate students in the engineering and physical sciences and supports independent study by researchers and professionals who must include uncertainty quantification and predictive science in the simulations they develop and/or perform.
Download or read book Quantitative Biology written by Brian Munsky and published by MIT Press. This book was released on 2018-08-21 with total page 729 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the quantitative modeling of biological processes, presenting modeling approaches, methodology, practical algorithms, software tools, and examples of current research. The quantitative modeling of biological processes promises to expand biological research from a science of observation and discovery to one of rigorous prediction and quantitative analysis. The rapidly growing field of quantitative biology seeks to use biology's emerging technological and computational capabilities to model biological processes. This textbook offers an introduction to the theory, methods, and tools of quantitative biology. The book first introduces the foundations of biological modeling, focusing on some of the most widely used formalisms. It then presents essential methodology for model-guided analyses of biological data, covering such methods as network reconstruction, uncertainty quantification, and experimental design; practical algorithms and software packages for modeling biological systems; and specific examples of current quantitative biology research and related specialized methods. Most chapters offer problems, progressing from simple to complex, that test the reader's mastery of such key techniques as deterministic and stochastic simulations and data analysis. Many chapters include snippets of code that can be used to recreate analyses and generate figures related to the text. Examples are presented in the three popular computing languages: Matlab, R, and Python. A variety of online resources supplement the the text. The editors are long-time organizers of the Annual q-bio Summer School, which was founded in 2007. Through the school, the editors have helped to train more than 400 visiting students in Los Alamos, NM, Santa Fe, NM, San Diego, CA, Albuquerque, NM, and Fort Collins, CO. This book is inspired by the school's curricula, and most of the contributors have participated in the school as students, lecturers, or both. Contributors John H. Abel, Roberto Bertolusso, Daniela Besozzi, Michael L. Blinov, Clive G. Bowsher, Fiona A. Chandra, Paolo Cazzaniga, Bryan C. Daniels, Bernie J. Daigle, Jr., Maciej Dobrzynski, Jonathan P. Doye, Brian Drawert, Sean Fancer, Gareth W. Fearnley, Dirk Fey, Zachary Fox, Ramon Grima, Andreas Hellander, Stefan Hellander, David Hofmann, Damian Hernandez, William S. Hlavacek, Jianjun Huang, Tomasz Jetka, Dongya Jia, Mohit Kumar Jolly, Boris N. Kholodenko, Markek Kimmel, Michał Komorowski, Ganhui Lan, Heeseob Lee, Herbert Levine, Leslie M Loew, Jason G. Lomnitz, Ard A. Louis, Grant Lythe, Carmen Molina-París, Ion I. Moraru, Andrew Mugler, Brian Munsky, Joe Natale, Ilya Nemenman, Karol Nienałtowski, Marco S. Nobile, Maria Nowicka, Sarah Olson, Alan S. Perelson, Linda R. Petzold, Sreenivasan Ponnambalam, Arya Pourzanjani, Ruy M. Ribeiro, William Raymond, William Raymond, Herbert M. Sauro, Michael A. Savageau, Abhyudai Singh, James C. Schaff, Boris M. Slepchenko, Thomas R. Sokolowski, Petr Šulc, Andrea Tangherloni, Pieter Rein ten Wolde, Philipp Thomas, Karen Tkach Tuzman, Lev S. Tsimring, Dan Vasilescu, Margaritis Voliotis, Lisa Weber
Download or read book The Quantified Scholar written by Juan Pablo Pardo-Guerra and published by Columbia University Press. This book was released on 2022-08-30 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since 1986, the British government, faced with dwindling budgets and growing calls for public accountability, has sought to assess the value of scholarly work in the nation’s universities. Administrators have periodically evaluated the research of most full-time academics employed in British universities, seeking to distribute increasingly scarce funding to those who use it best. How do such attempts to quantify the worth of knowledge change the nature of scholarship? Juan Pablo Pardo-Guerra examines the effects of quantitative research evaluations on British social scientists, arguing that the mission to measure academic excellence resulted in less diversity and more disciplinary conformity. Combining interviews and original computational analyses, The Quantified Scholar provides a compelling account of how scores, metrics, and standardized research evaluations altered the incentives of scientists and administrators by rewarding forms of scholarship that were closer to established disciplinary canons. In doing so, research evaluations amplified publication hierarchies and long-standing forms of academic prestige to the detriment of diversity. Slowly but surely, they reshaped academic departments, the interests of scholars, the organization of disciplines, and the employment conditions of researchers. Critiquing the effects of quantification on the workplace, this book also presents alternatives to existing forms of evaluation, calling for new forms of vocational solidarity that can challenge entrenched inequality in academia.
Download or read book Reproducibility and Replicability in Science written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2019-10-20 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Trust in Numbers written by Theodore M. Porter and published by Princeton University Press. This book was released on 2020-08-18 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: A foundational work on historical and social studies of quantification What accounts for the prestige of quantitative methods? The usual answer is that quantification is desirable in social investigation as a result of its successes in science. Trust in Numbers questions whether such success in the study of stars, molecules, or cells should be an attractive model for research on human societies, and examines why the natural sciences are highly quantitative in the first place. Theodore Porter argues that a better understanding of the attractions of quantification in business, government, and social research brings a fresh perspective to its role in psychology, physics, and medicine. Quantitative rigor is not inherent in science but arises from political and social pressures, and objectivity derives its impetus from cultural contexts. In a new preface, the author sheds light on the current infatuation with quantitative methods, particularly at the intersection of science and bureaucracy.
Download or read book Quantification a History of the Meaning of Measurement in the Natural and Social Sciences Proceedings of a Conference Held in the Offices of the Social Science Research Council New York 20 to 21 November 1959 written by new york Conference on the history of quantification in the sciences and published by . This book was released on 1961 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Quantification written by Harry Woolf and published by Irvington Pub. This book was released on 1961 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Interpretive Quantification written by J. Samuel Barkin and published by University of Michigan Press. This book was released on 2017-01-27 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: Revolutionary volume demonstrates how crossing the positivist and post-positivist divide improves political science research
Download or read book Subatomic quantification written by Marcin Wągiel and published by Language Science Press. This book was released on with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of this book is to explore the relationship between the cognitive notion of parthood and various grammatical devices expressing this concept in natural language. The monograph aims to investigate syntactic constructions and lexical categories, e.g., partitives, whole-adjectives, and multipliers, encoding different kinds of part-whole structures both in Slavic and non-Slavic languages. It is envisioned to inspire radical rethinking of the ontology of models accounting for nominal semantics. Specifically, it provides novel evidence for a mereotopological approach to meaning, i.e., a theory of wholes that captures not only parthood but also topological relations holding between parts. This evidence comes from the phenomenon of subatomic quantification, i.e., quantification over parts of referents of concrete count nouns.
Download or read book Quantifying the User Experience written by Jeff Sauro and published by Morgan Kaufmann. This book was released on 2016-07-12 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book The Seductions of Quantification written by Sally Engle Merry and published by University of Chicago Press. This book was released on 2016-06-10 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: We live in a world where seemingly everything can be measured. We rely on indicators to translate social phenomena into simple, quantified terms, which in turn can be used to guide individuals, organizations, and governments in establishing policy. Yet counting things requires finding a way to make them comparable. And in the process of translating the confusion of social life into neat categories, we inevitably strip it of context and meaning—and risk hiding or distorting as much as we reveal. With The Seductions of Quantification, leading legal anthropologist Sally Engle Merry investigates the techniques by which information is gathered and analyzed in the production of global indicators on human rights, gender violence, and sex trafficking. Although such numbers convey an aura of objective truth and scientific validity, Merry argues persuasively that measurement systems constitute a form of power by incorporating theories about social change in their design but rarely explicitly acknowledging them. For instance, the US State Department’s Trafficking in Persons Report, which ranks countries in terms of their compliance with antitrafficking activities, assumes that prosecuting traffickers as criminals is an effective corrective strategy—overlooking cultures where women and children are frequently sold by their own families. As Merry shows, indicators are indeed seductive in their promise of providing concrete knowledge about how the world works, but they are implemented most successfully when paired with context-rich qualitative accounts grounded in local knowledge.
Download or read book Basic Science Methods for Clinical Researchers written by Morteza Jalali and published by Academic Press. This book was released on 2017-03-31 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: Basic Science Methods for Clinical Researchers addresses the specific challenges faced by clinicians without a conventional science background. The aim of the book is to introduce the reader to core experimental methods commonly used to answer questions in basic science research and to outline their relative strengths and limitations in generating conclusive data. This book will be a vital companion for clinicians undertaking laboratory-based science. It will support clinicians in the pursuit of their academic interests and in making an original contribution to their chosen field. In doing so, it will facilitate the development of tomorrow's clinician scientists and future leaders in discovery science. - Serves as a helpful guide for clinical researchers who lack a conventional science background - Organized around research themes pertaining to key biological molecules, from genes, to proteins, cells, and model organisms - Features protocols, techniques for troubleshooting common problems, and an explanation of the advantages and limitations of a technique in generating conclusive data - Appendices provide resources for practical research methodology, including legal frameworks for using stem cells and animals in the laboratory, ethical considerations, and good laboratory practice (GLP)
Download or read book Uncertainty Quantification written by Luis Chase and published by Nova Science Publishers. This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent times, polynomial chaos expansion has emerged as a dominant technique to determine the response uncertainties of a system by propagating the uncertainties of the inputs. In this regard, the opening chapter of Uncertainty Quantification: Advances in Research and Applications, an intrusive approach called Galerkin Projection as well as non-intrusive approaches (such as pseudo-spectral projection and linear regression) are discussed.Next, the authors introduce a new methodology to determine the uncertainties of input parameters using CIRCÉ software to overcome the reliance on expert judgment. The goal is to determinate and evaluate the uncertainty bounds for physical models related to reflood model of MARS-KS code Vessel module (coupled with COBRA-TF) using both CIRCÉ and the experimental data of FEBA.Lastly, uncertainties related to rheological model parameters of skeletal muscles are modeled and analyzed, and available data are acquired and fused for hyperelastic constitutive model parameters with Neo-Hookean and Mooney-Rivlin formulations.
Download or read book Measurement in Psychology written by Joel Michell and published by Cambridge University Press. This book was released on 2005-10-20 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book traces how such a seemingly immutable idea as measurement proved so debatable when it collided with the subject matter of psychology. This book addresses philosophical and social influences (such as scientism, practicalism, and Pythagoreanism) reshaping the concept of measurement and identifies a fundamental problem at the core of this reshaping: the issue of whether psychological attributes really are quantitative. The author argues that the idea of measurement now endorsed within psychology actually subverts attempts to establish a genuinely quantitative science, and he urges a new direction. This volume relates views on measurement by thinkers such as Hölder, Russell, Campbell, and Nagel to earlier views, like those of Euclid and Oresme. Within the history of psychology, it considers contributions by Fechner, Cattell, Thorndike, Stevens and Suppes, among others. It also contains a nontechnical exposition of conjoint measurement theory and recent foundational work by leading measurement theorist R. Duncan Luce. This thought-provoking book will be particularly valued by researchers in the fields of psychological history and philosophy of science.
Download or read book Uncertainty Quantification written by Ralph C. Smith and published by SIAM. This book was released on 2013-12-02 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of uncertainty quantification is evolving rapidly because of increasing emphasis on models that require quantified uncertainties for large-scale applications, novel algorithm development, and new computational architectures that facilitate implementation of these algorithms. Uncertainty Quantification: Theory, Implementation, and Applications provides readers with the basic concepts, theory, and algorithms necessary to quantify input and response uncertainties for simulation models arising in a broad range of disciplines. The book begins with a detailed discussion of applications where uncertainty quantification is critical for both scientific understanding and policy. It then covers concepts from probability and statistics, parameter selection techniques, frequentist and Bayesian model calibration, propagation of uncertainties, quantification of model discrepancy, surrogate model construction, and local and global sensitivity analysis. The author maintains a complementary web page where readers can find data used in the exercises and other supplementary material.
