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Handbook of Analysis and Its Foundations is a self-contained and unified handbook on mathematical analysis and its foundations. Intended as a self-study guide for advanced undergraduates and beginning graduatestudents in mathematics and a reference for more advanced mathematicians, this highly readable book provides broader coverage than competing texts in the area. Handbook of Analysis and Its Foundations provides an introduction to a wide range of topics, including: algebra; topology; normed spaces; integration theory; topological vector spaces; and differential equations. The author effectively demonstrates the relationships between these topics and includes a few chapters on set theory and logic to explain the lack of examples for classical pathological objects whose existence proofs are not constructive. More complete than any other book on the subject, students will find this to be an invaluable handbook. Covers some hard-to-find results including: Bessagas and Meyers converses of the Contraction Fixed Point Theorem Redefinition of subnets by Aarnes and Andenaes Ghermans characterization of topological convergences Neumanns nonlinear Closed Graph Theorem van Maarens geometry-free version of Sperners Lemma Includes a few advanced topics in functional analysis Features all areas of the foundations of analysis except geometry Combines material usually found in many different sources, making this unified treatment more convenient for the user Has its own webpage: http://math.vanderbilt.edu/
Location analysis has matured from an area of theoretical inquiry that was designed to explain observed phenomena to a vibrant field which can be and has been used to locate items as diverse as landfills, fast food outlets, gas stations, as well as politicians and products in issue and feature spaces. Modern location science is dealt with by a diverse group of researchers and practitioners in geography, economics, operations research, industrial engineering, and computer science. Given the tremendous advances location science has seen from its humble beginnings, it is time to look back. The contributions in this volume were written by eminent experts in the field, each surveying the original contributions that created the field, and then providing an up-to-date review of the latest contributions. Specific areas that are covered in this volume include: • The three main fields of inquiry: minisum and minimax problems and covering models • Nonstandard location models, including those with competitive components, models that locate undesirable facilities, models with probabilistic features, and problems that allow interactions between facilities • Descriptions and detailed examinations of exact techniques including the famed Weiszfeld method, and heuristic methods ranging from Lagrangean techniques to Greedy algorithms • A look at the spheres of influence that the facilities generate and that attract customers to them, a topic crucial in planning retail facilities • The theory of central places, which, other than in mathematical games, where location science was born
This book develops the analysis of Time Series from its formal beginnings in the 1890s through to the publication of Box and Jenkins' watershed publication in 1970, showing how these methods laid the foundations for the modern techniques of Time Series analysis that are in use today.
This is an authoritative introduction to Computing Education research written by over 50 leading researchers from academia and the industry.
This Handbook gives a comprehensive snapshot of a field at the intersection of mathematics and computer science with applications in physics, engineering and education. Reviews 67 software systems and offers 100 pages on applications in physics, mathematics, computer science, engineering chemistry and education.
Edited by a diverse group of expert collaborators, the Handbook of the Cultural Foundations of Learning is a landmark volume that brings together cutting-edge research examining learning as entailing inherently cultural processes. Conceptualizing culture as both a set of social practices and connected to learner identities, the chapters synthesize contemporary research in elaborating a new vision of the cultural nature of learning, moving beyond summary to reshape the field toward studies that situate culture in the learning sciences alongside equity of educational processes and outcomes. With the recent increased focus on culture and equity within the educational research community, this volume presents a comprehensive, innovative treatment of what has become one of the field’s most timely and relevant topics.
This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.
Statistics and hypothesis testing are routinely used in areas (such as linguistics) that are traditionally not mathematically intensive. In such fields, when faced with experimental data, many students and researchers tend to rely on commercial packages to carry out statistical data analysis, often without understanding the logic of the statistical tests they rely on. As a consequence, results are often misinterpreted, and users have difficulty in flexibly applying techniques relevant to their own research — they use whatever they happen to have learned. A simple solution is to teach the fundamental ideas of statistical hypothesis testing without using too much mathematics. This book provides a non-mathematical, simulation-based introduction to basic statistical concepts and encourages readers to try out the simulations themselves using the source code and data provided (the freely available programming language R is used throughout). Since the code presented in the text almost always requires the use of previously introduced programming constructs, diligent students also acquire basic programming abilities in R. The book is intended for advanced undergraduate and graduate students in any discipline, although the focus is on linguistics, psychology, and cognitive science. It is designed for self-instruction, but it can also be used as a textbook for a first course on statistics. Earlier versions of the book have been used in undergraduate and graduate courses in Europe and the US. ”Vasishth and Broe have written an attractive introduction to the foundations of statistics. It is concise, surprisingly comprehensive, self-contained and yet quite accessible. Highly recommended.” Harald Baayen, Professor of Linguistics, University of Alberta, Canada ”By using the text students not only learn to do the specific things outlined in the book, they also gain a skill set that empowers them to explore new areas that lie beyond the book’s coverage.” Colin Phillips, Professor of Linguistics, University of Maryland, USA
Featuring contributions from leading scholars in the field, The Handbook of Narrative Analysis is the first comprehensive collection of sociolinguistic scholarship on narrative analysis to be published. Organized thematically to provide an accessible guide for how to engage with narrative without prescribing a rigid analytic framework Represents established modes of narrative analysis juxtaposed with innovative new methods for conducting narrative research Includes coverage of the latest advances in narrative analysis, from work on social media to small stories research Introduces and exemplifies a practice-based approach to narrative analysis that separates narrative from text so as to broaden the field beyond the printed page