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…
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Author : National Academies of Sciences, Engineering, and Medicine
Genre : Mathematics
Summary : 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.
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Author : Vladik Kreinovich
Genre : Technology & Engineering
Summary : 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.
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Author : National Academies of Sciences, Engineering, and Medicine
Genre : Science
Summary : 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.
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Author : Hong Jiao
Genre : Education
Summary : 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.
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Author : Jennifer Trusted
Genre : Philosophy
Summary :
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Author : National Academies of Sciences, Engineering, and Medicine
Genre : Education
Summary : 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.
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Author : Robert Hooke
Genre : Education
Summary : 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.
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Author : Wesley C. Salmon
Genre : Science
Summary :
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Author : Holger Andreas
Genre : Philosophy
Summary : This book covers work written by leading scholars from different schools within the research area of paraconsistency. The authors critically investigate how contemporary paraconsistent logics can be used to better understand human reasoning in science and mathematics. Offering a variety of perspectives, they shed a new light on the question of whether paraconsistent logics can function as the underlying logics of inconsistent but useful scientific and mathematical theories. The great variety of paraconsistent logics gives rise to various, interrelated questions, such as what are the desiderata a paraconsistent logic should satisfy, is there prospect of a universal approach to paraconsistent reasoning with axiomatic theories, and to what extent is reasoning about sets structurally analogous to reasoning about truth. Furthermore, the authors consider paraconsistent logic’s status as either a normative or descriptive discipline (or one which falls in between) and which inconsistent but non-trivial axiomatic theories are well understood by which types of paraconsistent approaches. This volume addresses such questions from different perspectives in order to (i) obtain a representative overview of the state of the art in the philosophical debate on paraconsistency, (ii) come up with fresh ideas for the future of paraconsistency, and most importantly (iii) provide paraconsistent logic with a stronger philosophical foundation, taking into account the developments within the different schools of paraconsistency.
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Author : Keith S. Taber
Genre : Education
Summary : "This book comprises a wide range of scholarly essays introducing readers to key topics and issues in science education. Science education has become a well established field in its own right, with a vast literature, and many active areas of scholarship. Science Education: An International Course Companion offers an entry point for students seeking a sound but introductory understanding of the key perspectives and areas of thinking in science education. Each account is self-contained and offers a scholarly and research-informed introduction to a particular topic, theme, or perspective, with both citations to key literature and recommendations for more advanced reading. Science Education: An International Course Companion allows readers (such as those preparing for school science teaching, or seeking more advanced specialist qualifications) to obtain a broad familiarity with key issues across the field as well as guiding wider reading about particular topics of interest. The book therefore acts as a reader to support learning across courses in science education internationally. The broad coverage of topics is such that that the book will support students following a diverse range of courses and qualifications. The comprehensive nature of the book will allow course leaders and departments to nominate the book as the key reader to support students – their core ‘course companion’ in science education."