Download or read book Refining the Concept of Scientific Inference When Working with Big Data written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2017-03-24 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: The concept of utilizing big data to enable scientific discovery has generated tremendous excitement and investment from both private and public sectors over the past decade, and expectations continue to grow. Using big data analytics to identify complex patterns hidden inside volumes of data that have never been combined could accelerate the rate of scientific discovery and lead to the development of beneficial technologies and products. However, producing actionable scientific knowledge from such large, complex data sets requires statistical models that produce reliable inferences (NRC, 2013). Without careful consideration of the suitability of both available data and the statistical models applied, analysis of big data may result in misleading correlations and false discoveries, which can potentially undermine confidence in scientific research if the results are not reproducible. In June 2016 the National Academies of Sciences, Engineering, and Medicine convened a workshop to examine critical challenges and opportunities in performing scientific inference reliably when working with big data. Participants explored new methodologic developments that hold significant promise and potential research program areas for the future. This publication summarizes the presentations and discussions from the workshop.
Download or read book Refining the Concept of Scientific Inference When Working with Big Data Proceedings of a Workshop in Brief written by and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Refining the Concept of Scientific Inference When Working with Big Data Proceedings of a Workshop in Brief written by and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Predictive Econometrics and Big Data written by Vladik Kreinovich and published by Springer. This book was released on 2017-11-30 with total page 788 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent research on predictive econometrics and big data. Gathering edited papers presented at the 11th International Conference of the Thailand Econometric Society (TES2018), held in Chiang Mai, Thailand, on January 10-12, 2018, its main focus is on predictive techniques – which directly aim at predicting economic phenomena; and big data techniques – which enable us to handle the enormous amounts of data generated by modern computers in a reasonable time. The book also discusses the applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that employs mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. It is therefore important to develop data processing techniques that explicitly focus on prediction. The more data we have, the better our predictions will be. As such, these techniques are essential to our ability to process huge amounts of available data.
Download or read book HQ Solutions written by NAHQ and published by Lippincott Williams & Wilkins. This book was released on 2017-10-16 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: For comprehensive guidance on creating quality structures that support patient/provider collaboration, cost-effective solutions, and safe, efficient care, get the fully updated HQ Solutions, an official publication of the National Association for Healthcare Quality (NAHQ). Written by HQ experts and applicable to all practice settings, this essential resource offers healthcare quality professionals the theoretical and practical basis for safe, reliable, cost-effective care, including the use of state-of-the-art tools for measuring, monitoring, selecting, and managing data. Invaluable for preparing for the Certified Professional in Healthcare Quality® (CPHQ) certification exam, this is an optimal healthcare quality professional’s resource. Create a safer, more efficient care environment, with proven quality improvement practices ... NEW quality and safety tools and techniques adaptable to any care setting NEW and updated content on recent changes in U.S. healthcare quality requirements, legislation, and reform NEW content on core skills and methods of organizational leadership, patient safety, performance and process improvement, and health data analytics Key resource for HQ principles and practices—vital for healthcare quality professionals including nurses, instructors, researchers, consultants, and clinicians in all practice settings, including home care, hospices, skilled nursing facilities, rehab, and ambulatory care, as well as healthcare organizations, healthcare boards, and government agencies Organizational Leadership Leadership fundamentals and principles, quality and safety infrastructure, strategic planning, and change management Real-life scenarios solved with proven leadership formulas and evidence-based solutions Performance measures, key performance and quality indicators, and performance improvement models Accreditation, Regulation, and Continuous Readiness Impact of regulations on healthcare quality and safety Continuous readiness activities Organizational assessment, survey procedures, and more Health Data Analytics Foundations of a solid data management system Tools, approaches, and application of data management systems, data collection, interpretation, and reporting Analysis tools and basic statistical techniques and methods Patient Safety Practical tools for safety assessment, planning, implementation, and evaluation Components of a safety culture Effective risk management strategies Performance, Safety, and Process Improvement Key principles and practices Critical pathways, effective team building, decision support, benchmarking IOM imperatives, analysis and interpretation of data, decision-support tools, and more
Download or read book Data Analytics and Psychometrics written by Hong Jiao and published by IAP. This book was released on 2018-12-01 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: The general theme of this book is to encourage the use of relevant methodology in data mining which is or could be applied to the interplay of education, statistics and computer science to solve psychometric issues and challenges in the new generation of assessments. In addition to item response data, other data collected in the process of assessment and learning will be utilized to help solve psychometric challenges and facilitate learning and other educational applications. Process data include those collected or available for collection during the process of assessment and instructional phase such as responding sequence data, log files, the use of help features, the content of web searches, etc. Some book chapters present the general exploration of process data in large-scale assessment. Further, other chapters also address how to integrate psychometrics and learning analytics in assessment and survey, how to use data mining techniques for security and cheating detection, how to use more assessment results to facilitate student’s learning and guide teacher’s instructional efforts. The book includes both theoretical and methodological presentations that might guide the future in this area, as well as illustrations of efforts to implement big data analytics that might be instructive to those in the field of learning and psychometrics. The context of the effort is diverse, including K-12, higher education, financial planning, and survey utilization. It is hoped that readers can learn from different disciplines, especially those who are specialized in assessment, would be critical to expand the ideas of what we can do with data analytics for informing assessment practices.
Download or read book Integrating Social and Behavioral Sciences Within the Weather Enterprise written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2018-01-05 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our ability to observe and forecast severe weather events has improved markedly over the past few decades. Forecasts of snow and ice storms, hurricanes and storm surge, extreme heat, and other severe weather events are made with greater accuracy, geographic specificity, and lead time to allow people and communities to take appropriate protective measures. Yet hazardous weather continues to cause loss of life and result in other preventable social costs. There is growing recognition that a host of social and behavioral factors affect how we prepare for, observe, predict, respond to, and are impacted by weather hazards. For example, an individual's response to a severe weather event may depend on their understanding of the forecast, prior experience with severe weather, concerns about their other family members or property, their capacity to take the recommended protective actions, and numerous other factors. Indeed, it is these factors that can determine whether or not a potential hazard becomes an actual disaster. Thus, it is essential to bring to bear expertise in the social and behavioral sciences (SBS)â€"including disciplines such as anthropology, communication, demography, economics, geography, political science, psychology, and sociologyâ€"to understand how people's knowledge, experiences, perceptions, and attitudes shape their responses to weather risks and to understand how human cognitive and social dynamics affect the forecast process itself. Integrating Social and Behavioral Sciences Within the Weather Enterprise explores and provides guidance on the challenges of integrating social and behavioral sciences within the weather enterprise. It assesses current SBS activities, describes the potential value of improved integration of SBS and barriers that impede this integration, develops a research agenda, and identifies infrastructural and institutional arrangements for successfully pursuing SBS-weather research and the transfer of relevant findings to operational settings.
Download or read book Graduate STEM Education for the 21st Century written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2018-08-21 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: The U.S. system of graduate education in science, technology, engineering, and mathematics (STEM) has served the nation and its science and engineering enterprise extremely well. Over the course of their education, graduate students become involved in advancing the frontiers of discovery, as well as in making significant contributions to the growth of the U.S. economy, its national security, and the health and well-being of its people. However, continuous, dramatic innovations in research methods and technologies, changes in the nature and availability of work, shifts in demographics, and expansions in the scope of occupations needing STEM expertise raise questions about how well the current STEM graduate education system is meeting the full array of 21st century needs. Indeed, recent surveys of employers and graduates and studies of graduate education suggest that many graduate programs do not adequately prepare students to translate their knowledge into impact in multiple careers. Graduate STEM Education for the 21st Century examines the current state of U.S. graduate STEM education. This report explores how the system might best respond to ongoing developments in the conduct of research on evidence-based teaching practices and in the needs and interests of its students and the broader society it seeks to serve. This will be an essential resource for the primary stakeholders in the U.S. STEM enterprise, including federal and state policymakers, public and private funders, institutions of higher education, their administrators and faculty, leaders in business and industry, and the students the system is intended to educate.
Download or read book Modern Interdisciplinary University Statistics Education written by National Research Council and published by National Academies Press. This book was released on 1994-02-01 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines how the discipline of statistics should respond to the changing environment in which statisticians work. What does the academic, industry, and government customer need? How can the content of courses and of the overall statistics educational experience be arranged to address the customer's needs? Interdisciplinary needs are described, and successful university programs in interdisciplinary statistics are detailed.
Download or read book Scientific Inference written by Harold Jeffreys and published by Cambridge University Press. This book was released on 1973-12-13 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: Logic and scientific inference; Probability; Sampling; Errors; Physical magnitudes; Mensuration; Newtonian dynamics; Light and relativity; Miscellaneous questions; Statistical mechanics and quantum theory.
Download or read book Scientific Inference Data Analysis and Robustness written by G. E. P. Box and published by Academic Press. This book was released on 2014-05-10 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematics Research Center Symposium: Scientific Inference, Data Analysis, and Robustness focuses on the philosophy of statistical modeling, including model robust inference and analysis of data sets. The selection first elaborates on pivotal inference and the conditional view of robustness and some philosophies of inference and modeling, including ideas on modeling, significance testing, and scientific discovery. The book then ponders on parametric empirical Bayes confidence intervals, ecumenism in statistics, and frequency properties of Bayes rules. Discussions focus on consistency of Bayes rules, scientific method and the human brain, and statistical estimation and criticism. The book takes a look at the purposes and limitations of data analysis, likelihood, shape, and adaptive inference, statistical inference and measurement of entropy, and the robustness of a hierarchical model for multinomials and contingency tables. Topics include numerical results for contingency tables and robustness, multinomials, flattening constants, and mixed Dirichlet priors, entropy and likelihood, and test as measurement of entropy. The selection is a valuable reference for researchers interested in robust inference and analysis of data sets.
Download or read book The Structure of Scientific Inference written by Mary Hesse and published by Univ of California Press. This book was released on 2022-05-13 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: This title is part of UC Press's Voices Revived program, which commemorates University of California Press’s mission to seek out and cultivate the brightest minds and give them voice, reach, and impact. Drawing on a backlist dating to 1893, Voices Revived makes high-quality, peer-reviewed scholarship accessible once again using print-on-demand technology. This title was originally published in 1974.
Download or read book Computer Age Statistical Inference written by Bradley Efron and published by Cambridge University Press. This book was released on 2016-07-21 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
Download or read book Introduction to Scientific Inference written by Robert Hooke and published by Praeger. This book was released on 1976-02-18 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inductive inference and "experimental error"; A population sample model: local inference; Expansion of the model: inference in the large; Expansion of the model: inference in the large; Interpretation of results; Random variables and distributions; Variance and related topics; Problems of sampling in physical situations; Randomization; Restricted randomization and experimental designs; Regression or curve fitting.
Download or read book Big Data at Work written by Scott Tonidandel and published by Routledge. This book was released on 2015-11-06 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: The amount of data in our world has been exploding, and analyzing large data sets—so called big data—will become a key basis of competition in business. Statisticians and researchers will be updating their analytic approaches, methods and research to meet the demands created by the availability of big data. The goal of this book is to show how advances in data science have the ability to fundamentally influence and improve organizational science and practice. This book is primarily designed for researchers and advanced undergraduate and graduate students in psychology, management and statistics.
Download or read book Scientific Inference Data Analysis and Robustness written by United States and published by . This book was released on 1983 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Big Data Meets Survey Science written by Craig A. Hill and published by John Wiley & Sons. This book was released on 2020-09-29 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offers a clear view of the utility and place for survey data within the broader Big Data ecosystem This book presents a collection of snapshots from two sides of the Big Data perspective. It assembles an array of tangible tools, methods, and approaches that illustrate how Big Data sources and methods are being used in the survey and social sciences to improve official statistics and estimates for human populations. It also provides examples of how survey data are being used to evaluate and improve the quality of insights derived from Big Data. Big Data Meets Survey Science: A Collection of Innovative Methods shows how survey data and Big Data are used together for the benefit of one or more sources of data, with numerous chapters providing consistent illustrations and examples of survey data enriching the evaluation of Big Data sources. Examples of how machine learning, data mining, and other data science techniques are inserted into virtually every stage of the survey lifecycle are presented. Topics covered include: Total Error Frameworks for Found Data; Performance and Sensitivities of Home Detection on Mobile Phone Data; Assessing Community Wellbeing Using Google Street View and Satellite Imagery; Using Surveys to Build and Assess RBS Religious Flag; and more. Presents groundbreaking survey methods being utilized today in the field of Big Data Explores how machine learning methods can be applied to the design, collection, and analysis of social science data Filled with examples and illustrations that show how survey data benefits Big Data evaluation Covers methods and applications used in combining Big Data with survey statistics Examines regulations as well as ethical and privacy issues Big Data Meets Survey Science: A Collection of Innovative Methods is an excellent book for both the survey and social science communities as they learn to capitalize on this new revolution. It will also appeal to the broader data and computer science communities looking for new areas of application for emerging methods and data sources.
