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Applied Modeling Techniques and Data Analysis 1
BIG DATA, ARTIFICIAL INTELLIGENCE AND DATA ANALYSIS SET Coordinated by Jacques Janssen
Data analysis is a scientific field that continues to grow enormously, most notably over the last few decades, following rapid growth within the tech industry, as well as the wide applicability of computational techniques alongside new advances in analytic tools. Modeling enables data analysts to identify relationships, make predictions, and to understand, interpret and visualize the extracted information more strategically.
This book includes the most recent advances on this topic, meeting increasing demand from wide circles of the scientific community. Applied Modeling Techniques and Data Analysis 1 is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians, working on the front end of data analysis and modeling applications. The chapters cover a cross section of current concerns and research interests in the above scientific areas. The collected material is divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with appropriate applications.
eBook
Data analysis and applications. 2, Utilization of results in Europe and other topics
\"This series of books collects a diverse array of work that provides the reader with theoretical and applied information on data analysis methods, models and techniques, along with appropriate applications. Volume 2 begins with an introductory chapter by Gilbert Saporta, a leading expert in the field, who summarizes the developments in data analysis over the last 50 years. The book is then divided into four parts: Part 1 examines (in)dependence relationships, innovation in the Nordic countries, dentistry journals, dependence among growth rates of GDP of V4 countries, emissions mitigation, and five-star ratings; Part 2 investigates access to credit for SMEs, gender-based impacts given Southern Europe's economic crisis, and labor market transition probabilities; Part 3 looks at recruitment at university job-placement offices and the Program for International Student Assessment; and Part 4 examines discriminants, PageRank, and the political spectrum of Germany.\"-- Provided by publisher.
Book
Decisions Over Decimals
Become a confident leader and use data, experience, and intuition to drive your decisions Agile decision making is imperative as you lead in a data-driven world. Amid streams of data and countless meetings, we make hasty decisions, slow decisions, and often no decisions. Uniquely bridging theory and practice, Decisions Over Decimals breaks this pattern by uniting data intelligence with human judgment to get to action — a sharp approach the authors refer to as Quantitative Intuition (QI). QI raises the power of thinking beyond big data without neglecting it and chasing the perfect decision while appreciating that such a thing can never really exist. Successful decision-makers are fierce interrogators. They square critical thinking with open-mindedness by blending information, intuition, and experience. Balancing these elements is at the heart of Decisions Over Decimals.
This book is not only designed to be read - but frequently referenced - as you face innumerable decision moments. It is the hands-on manual for confident, accurate decision-making you've been looking for; the rare resource that provides a set of pragmatic leadership tools to accelerate:
* Effectively framing the problem for stakeholders
* Synthesizing intelligence from incomplete information
* Delivering decisions that stick
Strike the right balance between information and intuition and lead the smarter way with the real-world guidance found in Decisions Over Decimals.
eBook
Literary Mathematics
Across the humanities and social sciences, scholars increasingly use quantitative methods to study textual data. Considered together, this research represents an extraordinary event in the long history of textuality. More or less all at once, the corpus has emerged as a major genre of cultural and scientific knowledge. In Literary Mathematics, Michael Gavin grapples with this development, describing how quantitative methods for the study of textual data offer powerful tools for historical inquiry and sometimes unexpected perspectives on theoretical issues of concern to literary studies.
Student-friendly and accessible, the book advances this argument through case studies drawn from the Early English Books Online corpus. Gavin shows how a copublication network of printers and authors reveals an uncannily accurate picture of historical periodization; that a vector-space semantic model parses historical concepts in incredibly fine detail; and that a geospatial analysis of early modern discourse offers a surprising panoramic glimpse into the period's notion of world geography. Across these case studies, Gavin challenges readers to consider why corpus-based methods work so effectively and asks whether the successes of formal modeling ought to inspire humanists to reconsider fundamental theoretical assumptions about textuality and meaning. As Gavin reveals, by embracing the expressive power of mathematics, scholars can add new dimensions to digital humanities research and find new connections with the social sciences.
eBook
Quantitative methods for health research
A practical introduction to epidemiology, biostatistics, and research methodology for the whole health care community
This comprehensive text, which has been extensively revised with new material and additional topics, utilizes a practical slant to introduce health professionals and students to epidemiology, biostatistics, and research methodology. It draws examples from a wide range of topics, covering all of the main contemporary health research methods, including survival analysis, Cox regression, and systematic reviews and meta-analysis—the explanation of which go beyond introductory concepts. This second edition of Quantitative Methods for Health Research: A Practical Interactive Guide to Epidemiology and Statistics also helps develop critical skills that will prepare students to move on to more advanced and specialized methods.
A clear distinction is made between knowledge and concepts that all students should ensure they understand, and those that can be pursued further by those who wish to do so. Self-assessment exercises throughout the text help students explore and reflect on their understanding. A program of practical exercises in SPSS (using a prepared data set) helps to consolidate the theory and develop skills and confidence in data handling, analysis, and interpretation. Highlights of the book include:
* Combining epidemiology and bio-statistics to demonstrate the relevance and strength of statistical methods
* Emphasis on the interpretation of statistics using examples from a variety of public health and health care situations to stress relevance and application
* Use of concepts related to examples of published research to show the application of methods and balance between ideals and the realities of research in practice
* Integration of practical data analysis exercises to develop skills and confidence
* Supplementation by a student companion website which provides guidance on data handling in SPSS and study data sets as referred to in the text
Quantitative Methods for Health Research, Second Edition is a practical learning resource for students, practitioners and researchers in public health, health care and related disciplines, providing both a course book and a useful introductory reference.
eBook
Model identification and data analysis
This book is about constructing models from experimental data. It covers a range of topics, from statistical data prediction to Kalman filtering, from black-box model identification to parameter estimation, from spectral analysis to predictive control.Written for graduate students, this textbook offers an approach that has proven successful throughout the many years during which its author has taught these topics at his University.The book:Contains accessible methods explained step-by-step in simple termsOffers an essential tool useful in a variety of fields, especially engineering, statistics, and mathematicsIncludes an overview on random variables and stationary processes, as well as an introduction to discrete time models and matrix analysisIncorporates historical commentaries to put into perspective the developments that have brought the discipline to its current stateProvides many examples and solved problems to complement the presentation and facilitate comprehension of the techniques presented
eBook