Download or read book Statistical Paradigms Recent Advances And Reconciliations written by Ashis Sengupta and published by World Scientific. This book was released on 2014-10-03 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume consists of a collection of research articles on classical and emerging Statistical Paradigms — parametric, non-parametric and semi-parametric, frequentist and Bayesian — encompassing both theoretical advances and emerging applications in a variety of scientific disciplines. For advances in theory, the topics include: Bayesian Inference, Directional Data Analysis, Distribution Theory, Econometrics and Multiple Testing Procedures. The areas in emerging applications include: Bioinformatics, Factorial Experiments and Linear Models, Hotspot Geoinformatics and Reliability.

Download or read book Statistical Evidence written by Richard Royall and published by Routledge. This book was released on 2017-11-22 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interpreting statistical data as evidence, Statistical Evidence: A Likelihood Paradigm focuses on the law of likelihood, fundamental to solving many of the problems associated with interpreting data in this way. Statistics has long neglected this principle, resulting in a seriously defective methodology. This book redresses the balance, explaining why science has clung to a defective methodology despite its well-known defects. After examining the strengths and weaknesses of the work of Neyman and Pearson and the Fisher paradigm, the author proposes an alternative paradigm which provides, in the law of likelihood, the explicit concept of evidence missing from the other paradigms. At the same time, this new paradigm retains the elements of objective measurement and control of the frequency of misleading results, features which made the old paradigms so important to science. The likelihood paradigm leads to statistical methods that have a compelling rationale and an elegant simplicity, no longer forcing the reader to choose between frequentist and Bayesian statistics.

Download or read book Utilizing Big Data Paradigms for Business Intelligence written by Darmont, Jérôme and published by IGI Global. This book was released on 2018-08-10 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: Because efficient compilation of information allows managers and business leaders to make the best decisions for the financial solvency of their organizations, data analysis is an important part of modern business administration. Understanding the use of analytics, reporting, and data mining in everyday business environments is imperative to the success of modern businesses. Utilizing Big Data Paradigms for Business Intelligence is a pivotal reference source that provides vital research on how to address the challenges of data extraction in business intelligence using the five “Vs” of big data: velocity, volume, value, variety, and veracity. This book is ideally designed for business analysts, investors, corporate managers, entrepreneurs, and researchers in the fields of computer science, data science, and business intelligence.

Download or read book Data Mining Foundations and Intelligent Paradigms written by Dawn E. Holmes and published by Springer Science & Business Media. This book was released on 2011-11-09 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled “DATA MINING: Foundations and Intelligent Paradigms: Volume 2: Core Topics including Statistical, Time-Series and Bayesian Analysis” we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.

Download or read book Christian and Humanist Foundations for Statistical Inference written by Andrew M. Hartley and published by Wipf and Stock Publishers. This book was released on 2007-12-01 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Philosophy of the Law Idea (PLI) analyzes the manner in which religious beliefs control scientific theorizing. Religious beliefs control philosophical overviews of reality. Overviews of reality, also called ontologies, try to discover and disclose the essential nature of reality. They are concerned with what kinds of things exist and with the connections between the various types of properties and laws in human experience. Among such overviews are the biblically consistent overview provided by the PLI and certain humanist mathematicist and subjectivist overviews. The science of statistical inference seeks to evaluate the credibility of scientific hypotheses given empirical data. This essay reviews various popular paradigms, or systems of theories, concerning the ways that credibility may be evaluated, and identifies some ways that these religiously controlled overviews of reality have, in turn, controlled statistical paradigms. In particular, one paradigm harmonizes with the PLI's overview; another, with the subjectivist overview; and two others, with the mathematicist overview.

Download or read book Machine Learning and Big Data Analytics Paradigms Analysis Applications and Challenges written by Aboul Ella Hassanien and published by Springer Nature. This book was released on 2020-12-14 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.

Download or read book Research Paradigms and Their Methodological Alignment in Social Sciences written by Bunmi Isaiah Omodan and published by Taylor & Francis. This book was released on 2024-08-01 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research Paradigms and Their Methodological Alignment in Social Sciences is a comprehensive guide addressing the common conceptions surrounding research paradigms. This practical book demystifies complex concepts, giving researchers a nuanced understanding of the significance of research paradigms. It offers detailed insights, examples, and strategies for selecting and applying appropriate research methods, aiming to enhance the rigour and impact of scholarly work. This insightful guide meticulously explores the intricacies of research paradigms in the social sciences. It begins by unravelling the concept and historical development of research paradigm, emphasising its pivotal role in shaping the research process. The book elucidates major research paradigms, including positivism, interpretivism, transformative paradigm, postcolonial indigenous paradigm, and pragmatism. Each paradigm is dissected, unveiling philosophical underpinnings, methodological designs, and critical considerations. The chapters carefully align research questions with specific paradigms through illustrative case studies, offering practical guidance for researchers at all levels. Notably, the transformative paradigm and postcolonial indigenous perspective receive dedicated attention, addressing their unique methodological nuances and ethical dimensions. The exploration extends to pragmatism, seamlessly integrating theoretical foundations with real-world applications. The book strives to bridge the awareness gap in academic settings, fostering a profound appreciation for research paradigms and promoting a thoughtful, rigorous approach to scholarly inquiry. This book caters to students, novice and experienced researchers, offering a comprehensive understanding of research paradigms. It's valuable for academia, aiding undergraduate and postgraduate students, educators, and researchers in various disciplines. Research organisations, academic institutions, and professionals in diverse fields engaged in research and development will also find it a valuable resource.

Download or read book Philosophy of Statistics written by and published by Elsevier. This book was released on 2011-05-31 with total page 1260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statisticians and philosophers of science have many common interests but restricted communication with each other. This volume aims to remedy these shortcomings. It provides state-of-the-art research in the area of philosophy of statistics by encouraging numerous experts to communicate with one another without feeling “restricted by their disciplines or thinking “piecemeal in their treatment of issues. A second goal of this book is to present work in the field without bias toward any particular statistical paradigm. Broadly speaking, the essays in this Handbook are concerned with problems of induction, statistics and probability. For centuries, foundational problems like induction have been among philosophers’ favorite topics; recently, however, non-philosophers have increasingly taken a keen interest in these issues. This volume accordingly contains papers by both philosophers and non-philosophers, including scholars from nine academic disciplines. Provides a bridge between philosophy and current scientific findings Covers theory and applications Encourages multi-disciplinary dialogue

Download or read book Machine Learning Paradigms written by Aristomenis S. Lampropoulos and published by Springer. This book was released on 2015-06-13 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: This timely book presents Applications in Recommender Systems which are making recommendations using machine learning algorithms trained via examples of content the user likes or dislikes. Recommender systems built on the assumption of availability of both positive and negative examples do not perform well when negative examples are rare. It is exactly this problem that the authors address in the monograph at hand. Specifically, the books approach is based on one-class classification methodologies that have been appearing in recent machine learning research. The blending of recommender systems and one-class classification provides a new very fertile field for research, innovation and development with potential applications in “big data” as well as “sparse data” problems. The book will be useful to researchers, practitioners and graduate students dealing with problems of extensive and complex data. It is intended for both the expert/researcher in the fields of Pattern Recognition, Machine Learning and Recommender Systems, as well as for the general reader in the fields of Applied and Computer Science who wishes to learn more about the emerging discipline of Recommender Systems and their applications. Finally, the book provides an extended list of bibliographic references which covers the relevant literature completely.

Download or read book Statistical Evidence written by Richard M. Royall and published by . This book was released on 1997 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Data Science Framework written by Juan J. Cuadrado-Gallego and published by Springer Nature. This book was released on 2020-10-01 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book first consolidates the results of the EU-funded EDISON project (Education for Data Intensive Science to Open New science frontiers), which developed training material and information to assist educators, trainers, employers, and research infrastructure managers in identifying, recruiting and inspiring the data science professionals of the future. It then deepens the presentation of the information and knowledge gained to allow for easier assimilation by the reader. The contributed chapters are presented in sequence, each chapter picking up from the end point of the previous one. After the initial book and project overview, the chapters present the relevant data science competencies and body of knowledge, the model curriculum required to teach the required foundations, profiles of professionals in this domain, and use cases and applications. The text is supported with appendices on related process models. The book can be used to develop new courses in data science, evaluate existing modules and courses, draft job descriptions, and plan and design efficient data-intensive research teams across scientific disciplines.

Download or read book Emerging Methods and Paradigms in Scholarship and Education Research written by Ling, Lorraine and published by IGI Global. This book was released on 2019-08-30 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a renaissance in the use of the term “scholarship,” as it is being used to define areas of academic endeavour, describe academic work and achievements, and measure the quality of higher education. Although all academicians are required to engage in scholarship, it is difficult to navigate as there is a misunderstanding of this concept as new methods and approaches emerge. Emerging Methods and Paradigms in Scholarship and Education Research is an essential academic book that is designed to explain the areas of scholarship and their contemporary relationship to key components of academic work: research, teaching, service, and engagement. The chapter authors explore conceptions of scholarship, paradigms, and methods that fit a variety of contexts and needs. Highlighting a wide range of approaches from scientific realism and neo-positivism to interpretative, transformative, and pragmatic educational strategies and policy, this book is ideal for researchers, teachers, educational leaders, academicians, educational policymakers, and quality assurance agencies.

Download or read book Register based Statistics written by Anders Wallgren and published by John Wiley & Sons. This book was released on 2014-04-01 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive and up to date treatment of theory and practical implementation in Register-based statistics. It begins by defining the area, before explaining how to structure such systems, as well as detailing alternative approaches. It explains how to create statistical registers, how to implement quality assurance, and the use of IT systems for register-based statistics. Further to this, clear details are given about the practicalities of implementing such statistical methods, such as protection of privacy and the coordination and coherence of such an undertaking. This edition offers a full understanding of both the principles and practices of this increasingly popular area of statistics, and can be considered a first step to a more systematic way of working with register-statistical issues. This book addresses the growing global interest in the topic and employs a much broader, more international approach than the 1st edition. New chapters explore different kinds of register-based surveys, such as preconditions for register-based statistics and comparing sample survey and administrative data. Furthermore, the authors present discussions on register-based census, national accounts and the transition towards a register-based system as well as presenting new chapters on quality assessment of administrative sources and production process quality.

Download or read book Statistical Inference as Severe Testing written by Deborah G. Mayo and published by Cambridge University Press. This book was released on 2018-09-20 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.

Download or read book Implementation of Machine Learning Algorithms Using Control Flow and Dataflow Paradigms written by Milutinovi?, Veljko and published by IGI Global. This book was released on 2022-03-11 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on current literature and cutting-edge advances in the machine learning field, there are four algorithms whose usage in new application domains must be explored: neural networks, rule induction algorithms, tree-based algorithms, and density-based algorithms. A number of machine learning related algorithms have been derived from these four algorithms. Consequently, they represent excellent underlying methods for extracting hidden knowledge from unstructured data, as essential data mining tasks. Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms presents widely used data-mining algorithms and explains their advantages and disadvantages, their mathematical treatment, applications, energy efficient implementations, and more. It presents research of energy efficient accelerators for machine learning algorithms. Covering topics such as control-flow implementation, approximate computing, and decision tree algorithms, this book is an essential resource for computer scientists, engineers, students and educators of higher education, researchers, and academicians.

Download or read book Innovative Statistical Methods for Public Health Data written by Ding-Geng (Din) Chen and published by Springer. This book was released on 2015-08-31 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book brings together experts working in public health and multi-disciplinary areas to present recent issues in statistical methodological development and their applications. This timely book will impact model development and data analyses of public health research across a wide spectrum of analysis. Data and software used in the studies are available for the reader to replicate the models and outcomes. The fifteen chapters range in focus from techniques for dealing with missing data with Bayesian estimation, health surveillance and population definition and implications in applied latent class analysis, to multiple comparison and meta-analysis in public health data. Researchers in biomedical and public health research will find this book to be a useful reference and it can be used in graduate level classes.

Download or read book Probability and Forensic Evidence written by Ronald Meester and published by Cambridge University Press. This book was released on 2021-04-08 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the role of statistics and probability in the evaluation of forensic evidence, including both theoretical issues and applications in legal contexts. It discusses what evidence is and how it can be quantified, how it should be understood, and how it is applied (and, sometimes, misapplied). After laying out their philosophical position, the authors begin with a detailed study of the likelihood ratio. Following this grounding, they discuss applications of the likelihood ratio to forensic questions, in the abstract and in concrete cases. The analysis of DNA evidence in particular is treated in great detail. Later chapters concern Bayesian networks, frequentist approaches to evidence, the use of belief functions, and the thorny subject of database searches and familial searching. Finally, the authors provide commentary on various recommendation reports for forensic science. Written to be accessible to a wide audience of applied mathematicians, forensic scientists, and scientifically-oriented legal scholars, this book is a must-read for all those interested in the mathematical and philosophical foundations of evidence and belief.