Trends And Challenges In Categorical Data Analysis
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Lectures On Advanced Topics In Categorical Data Analysis
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Author : Tamás Rudas
language : en
Publisher: Springer Nature
Release Date : 2024-12-16
Lectures On Advanced Topics In Categorical Data Analysis written by Tamás Rudas and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-16 with Mathematics categories.
This book continues the mission of the previous text by the author, Lectures on Categorical Data Analysis, by expanding on the introductory concepts from that volume and providing a mathematically rigorous presentation of advanced topics and current research in statistical techniques which can be applied in the social, political, behavioral, and life sciences. It presents an intuitive and unified discussion of an array of themes in categorical data analysis, and the emphasis on structure over stochastics renders many of the methods applicable in machine learning environments and for the analysis of big data. The book focuses on graphical models, their application in causal analysis, the analytical properties of parameterizations of multivariate discrete distributions, marginal models, and coordinate-free relational models. To guide the readers in future research, the volume provides references to original papers and also offers detailed proofs of most of the significant results. Like the previous volume, it features exercises and research questions, making it appropriate for graduate students, as well as for active researchers.
Trends And Challenges In Categorical Data Analysis
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Author : Maria Kateri
language : en
Publisher:
Release Date : 2023
Trends And Challenges In Categorical Data Analysis written by Maria Kateri and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
This book provides a selection of modern and sophisticated methodologies for the analysis of large and complex univariate and multivariate categorical data. It gives an overview of a substantive and broad collection of topics in the analysis of categorical data, including association, marginal and graphical models, time series and fixed effects models, as well as modern methods of estimation such as regularization, Bayesian estimation and bias reduction methods, along with new simple measures for model interpretability. Methodological innovations and developments are illustrated and explained through real-world applications, together with useful R packages, allowing readers to replicate most of the analyses using the provided code. The applications span a variety of disciplines, including education, psychology, health, economics, and social sciences.
Statistical Learning And Modeling In Data Analysis
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Author : Simona Balzano
language : en
Publisher: Springer Nature
Release Date : 2021-07-13
Statistical Learning And Modeling In Data Analysis written by Simona Balzano and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-13 with Mathematics categories.
The contributions gathered in this book focus on modern methods for statistical learning and modeling in data analysis and present a series of engaging real-world applications. The book covers numerous research topics, ranging from statistical inference and modeling to clustering and factorial methods, from directional data analysis to time series analysis and small area estimation. The applications reflect new analyses in a variety of fields, including medicine, finance, engineering, marketing and cyber risk. The book gathers selected and peer-reviewed contributions presented at the 12th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2019), held in Cassino, Italy, on September 11–13, 2019. CLADAG promotes advanced methodological research in multivariate statistics with a special focus on data analysis and classification, and supports the exchange and dissemination of ideas, methodological concepts, numerical methods, algorithms, and computational and applied results. This book, true to CLADAG’s goals, is intended for researchers and practitioners who are interested in the latest developments and applications in the field of data analysis and classification.
Mastering Categorical Data Analysis
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Author : Pasquale De Marco
language : en
Publisher: Pasquale De Marco
Release Date : 2025-03-10
Mastering Categorical Data Analysis written by Pasquale De Marco and has been published by Pasquale De Marco this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-10 with Science categories.
In the realm of data analysis, categorical data holds a prominent place, encompassing a vast array of information from customer preferences to medical diagnoses. "Mastering Categorical Data Analysis" is a comprehensive guide that empowers readers to unlock the secrets hidden within this complex data type. Written in a clear and engaging style, this book provides a thorough exploration of the fundamental concepts, methods, and applications of categorical data analysis. It is meticulously crafted for a wide audience, catering to statisticians, data scientists, researchers, and students alike. With its in-depth coverage, "Mastering Categorical Data Analysis" delves into the core principles of probability distributions and measures of association, laying the groundwork for understanding the relationships between categorical variables. It then progresses to more advanced techniques, such as log-linear models and latent class analysis, equipping readers with the tools to tackle even the most intricate data challenges. Throughout the book, practical examples and real-world case studies illuminate the concepts and methods discussed. These case studies span a diverse range of fields, including healthcare, social sciences, business, and environmental sciences, showcasing the versatility and impact of categorical data analysis in addressing real-world problems. Moreover, the book delves into recent developments and future directions in the field, keeping readers abreast of the latest advancements and emerging trends. It also addresses the ethical considerations that arise when working with categorical data, ensuring that readers are equipped to handle data responsibly and ethically. By the end of this comprehensive journey, readers will have gained a deep understanding of categorical data analysis and the ability to apply it effectively to solve complex problems. They will be empowered to make informed decisions, uncover hidden patterns, and extract meaningful insights from their data, unlocking the full potential of categorical data analysis. "Mastering Categorical Data Analysis" is an invaluable resource for anyone seeking to master this powerful technique. It is a key to unlocking the secrets of categorical data, enabling readers to transform raw data into actionable insights and drive informed decision-making. If you like this book, write a review!
Statistics For The 21st Century
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Author : Gabor Szekely
language : en
Publisher: CRC Press
Release Date : 2000-01-25
Statistics For The 21st Century written by Gabor Szekely and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-01-25 with Mathematics categories.
A selection of articles presented at the Eighth Lukacs Symposium held at the Bowling Green State University, Ohio. They discuss consistency and accuracy of the sequential bootstrap, hypothesis testing, geometry in multivariate analysis, the classical extreme value model, the analysis of cross-classified data, diffusion models for neural activity, e
Comprehensive Guide To Statistics
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Author : Mohit Chatterjee
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Comprehensive Guide To Statistics written by Mohit Chatterjee and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Science categories.
This comprehensive textbook offers an in-depth exploration of various topics in statistics, ranging from probability theory and statistical inference to machine learning and data analysis. It balances theoretical rigor and practical applications, catering to both undergraduate and graduate students, as well as professionals in the field of statistics and related disciplines. The book begins with foundational concepts in probability theory, covering random variables, probability distributions, and expectation. It then delves into statistical inference, discussing estimation, hypothesis testing, and regression analysis. Advanced topics like Bayesian statistics, machine learning algorithms, and resampling methods are also explored. Key strengths of this textbook include clear and concise explanations, numerous examples, and exercises to reinforce learning. The accessible yet rigorous writing style makes complex concepts understandable to readers at various levels of expertise. Modern computational tools and techniques are incorporated, emphasizing practical aspects of statistical analysis in the era of big data. Readers are encouraged to apply their knowledge using software packages like R and Python, enhancing their skills in data analysis and interpretation. This comprehensive and authoritative textbook covers a wide range of topics in statistics, making it an indispensable resource for students, researchers, and practitioners alike. It provides a solid foundation in statistical theory and its real-world applications.
Handbook Of Research On Technical Privacy And Security Challenges In A Modern World
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Author : Tyagi, Amit Kumar
language : en
Publisher: IGI Global
Release Date : 2022-06-30
Handbook Of Research On Technical Privacy And Security Challenges In A Modern World written by Tyagi, Amit Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-30 with Computers categories.
More individuals than ever are utilizing internet technologies to work from home, teach and learn, shop, interact with peers, review medical records, and more. While it is certainly convenient to conduct such tasks via the internet, this increased internet presence has also led to a rise in the search and availability of personal information, which in turn is resulting in more cyber-attacks, privacy breaches, and information leaks. Cyber criminals are using such opportunities to attack governments, organizations, and individuals, making it necessary to anticipate, assess, and mitigate privacy and security threats during this infodemic. The Handbook of Research on Technical, Privacy, and Security Challenges in a Modern World discusses the design and development of different machine learning systems, including next generation applications, in order to mitigate cyber-attacks and address security challenges in everyday technologies. It further explores select methods and algorithms of learning for implementing better security methods in fields such as business and healthcare. It recognizes the future of privacy and the importance of preserving data through recommended practice, feedback loops, and smart agents. Covering topics such as face mask detection, gesture recognition, and botnet attacks and detection, this major reference work is a dynamic resource for medical professionals, healthcare administrators, government officials, business executives and managers, IT managers, students and faculty of higher education, librarians, researchers, and academicians.
The Art Of Modelling The Learning Process
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Author : Jimmie Leppink
language : en
Publisher: Springer Nature
Release Date : 2020-04-06
The Art Of Modelling The Learning Process written by Jimmie Leppink and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-06 with Education categories.
By uniting key concepts and methods from education, psychology, statistics, econometrics, medicine, language, and forensic science, this textbook provides an interdisciplinary methodological approach to study human learning processes longitudinally. This longitudinal approach can help to acquire a better understanding of learning processes, can inform both future learning and the revision of educational content and formats, and may help to foster self-regulated learning skills. The initial section of this textbook focuses on different types of research questions as well as practice-driven questions that may refer to groups or to individual learners. This is followed by a discussion of different types of outcome variables in educational research and practice, such as pass/fail and other dichotomies, multi-category nominal choices, ordered performance categories, and different types of quantifiable (i.e., interval or ratio level of measurement) variables. For each of these types of outcome variables, single-measurement and repeated-measurements scenarios are offered with clear examples. The book then introduces cross-sectional and longitudinal interdependence of learning-related variables through emerging network-analytic methods and in the final part the learned concepts are applied to different types of studies involving time series. The book concludes with some general guidelines to give direction to future (united) educational research and practice. This textbook is a must-have for all applied researchers, teachers and practitioners interested in (the teaching of) human learning, instructional design, assessment, life-long learning or applications of concepts and methods commonly encountered in fields such as econometrics, psychology, and sociology to educational research and practice.
An Introduction To Categorical Data Analysis
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Author : Alan Agresti
language : en
Publisher: John Wiley & Sons
Release Date : 2018-11-20
An Introduction To Categorical Data Analysis written by Alan Agresti and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-20 with Mathematics categories.
A valuable new edition of a standard reference The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data. Adding to the value in the new edition is: • Illustrations of the use of R software to perform all the analyses in the book • A new chapter on alternative methods for categorical data, including smoothing and regularization methods (such as the lasso), classification methods such as linear discriminant analysis and classification trees, and cluster analysis • New sections in many chapters introducing the Bayesian approach for the methods of that chapter • More than 70 analyses of data sets to illustrate application of the methods, and about 200 exercises, many containing other data sets • An appendix showing how to use SAS, Stata, and SPSS, and an appendix with short solutions to most odd-numbered exercises Written in an applied, nontechnical style, this book illustrates the methods using a wide variety of real data, including medical clinical trials, environmental questions, drug use by teenagers, horseshoe crab mating, basketball shooting, correlates of happiness, and much more. An Introduction to Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and biostatisticians as well as methodologists in the social and behavioral sciences, medicine and public health, marketing, education, and the biological and agricultural sciences.
Cybersecurity Data Science
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Author : Scott Mongeau
language : en
Publisher: Springer Nature
Release Date : 2021-10-01
Cybersecurity Data Science written by Scott Mongeau and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-01 with Computers categories.
This book encompasses a systematic exploration of Cybersecurity Data Science (CSDS) as an emerging profession, focusing on current versus idealized practice. This book also analyzes challenges facing the emerging CSDS profession, diagnoses key gaps, and prescribes treatments to facilitate advancement. Grounded in the management of information systems (MIS) discipline, insights derive from literature analysis and interviews with 50 global CSDS practitioners. CSDS as a diagnostic process grounded in the scientific method is emphasized throughout Cybersecurity Data Science (CSDS) is a rapidly evolving discipline which applies data science methods to cybersecurity challenges. CSDS reflects the rising interest in applying data-focused statistical, analytical, and machine learning-driven methods to address growing security gaps. This book offers a systematic assessment of the developing domain. Advocacy is provided to strengthen professional rigor and best practices in the emerging CSDS profession. This book will be of interest to a range of professionals associated with cybersecurity and data science, spanning practitioner, commercial, public sector, and academic domains. Best practices framed will be of interest to CSDS practitioners, security professionals, risk management stewards, and institutional stakeholders. Organizational and industry perspectives will be of interest to cybersecurity analysts, managers, planners, strategists, and regulators. Research professionals and academics are presented with a systematic analysis of the CSDS field, including an overview of the state of the art, a structured evaluation of key challenges, recommended best practices, and an extensive bibliography.