Assignment Methods in Combinational Data Analysis

Assignment Methods in Combinational Data Analysis PDF Author: Lawrence Hubert
Publisher: CRC Press
ISBN: 9780824776176
Category : Mathematics
Languages : en
Pages : 350

Book Description
For the first time in one text, this handy pedagogical reference presents comprehensive inference strategies for organizing disparate nonparametric statistics topics under one scheme, illustrating ways of analyzing data sets based on generic notions of proximity (of "closeness") between objects. Assignment Methods in Combinatorial Data Analysis specifically reviews both linear and quadratic assignment models ... covers extensions to multiple object sets and higher-order assignment indices ... considers methods of applying linear assignment models in common data analysis contexts ... discusses a second motion of assignment (or "matching") based upon pairs of objects ... explores confirmatory methods of augmenting multidimensional sealing, cluster analysis, and related techniques ... labels sections in order of priority for continuity and convenience ... and includes extensive bibliographies of related literature. Assignment Methods in Combinatorial Data Analysis gives authoritative coverage of statistical testing, and measures of association in a single source. It is required reading and an invaluable reference for researchers and graduate students in the behavioral and social sciences using quantitative methods of data representation. Book jacket.

American Doctoral Dissertations

American Doctoral Dissertations PDF Author:
Publisher:
ISBN:
Category : Dissertation abstracts
Languages : en
Pages : 776

Book Description


Proximity and Preference

Proximity and Preference PDF Author: Reginald G. Golledge
Publisher: U of Minnesota Press
ISBN: 1452911320
Category :
Languages : en
Pages : 357

Book Description


Unidimensional Scaling

Unidimensional Scaling PDF Author: John McIver
Publisher: SAGE
ISBN: 9780803917361
Category : Mathematics
Languages : en
Pages : 100

Book Description
This series of methodological works provides introductory explanations and demonstrations of various data analysis techniques applicable to the social sciences. Designed for readers with a limited background in statistics or mathematics, this series aims to make the assumptions and practices of quantitative analysis more readily accessible.

Correspondence Analysis and Data Coding with Java and R

Correspondence Analysis and Data Coding with Java and R PDF Author: Fionn Murtagh
Publisher: CRC Press
ISBN: 1420034944
Category : Mathematics
Languages : en
Pages : 253

Book Description
Developed by Jean-Paul Benzerci more than 30 years ago, correspondence analysis as a framework for analyzing data quickly found widespread popularity in Europe. The topicality and importance of correspondence analysis continue, and with the tremendous computing power now available and new fields of application emerging, its significance is greater

Mathematical Classification and Clustering

Mathematical Classification and Clustering PDF Author: Boris Mirkin
Publisher: Springer Science & Business Media
ISBN: 1461304571
Category : Mathematics
Languages : en
Pages : 439

Book Description
I am very happy to have this opportunity to present the work of Boris Mirkin, a distinguished Russian scholar in the areas of data analysis and decision making methodologies. The monograph is devoted entirely to clustering, a discipline dispersed through many theoretical and application areas, from mathematical statistics and combina torial optimization to biology, sociology and organizational structures. It compiles an immense amount of research done to date, including many original Russian de velopments never presented to the international community before (for instance, cluster-by-cluster versions of the K-Means method in Chapter 4 or uniform par titioning in Chapter 5). The author's approach, approximation clustering, allows him both to systematize a great part of the discipline and to develop many in novative methods in the framework of optimization problems. The optimization methods considered are proved to be meaningful in the contexts of data analysis and clustering. The material presented in this book is quite interesting and stimulating in paradigms, clustering and optimization. On the other hand, it has a substantial application appeal. The book will be useful both to specialists and students in the fields of data analysis and clustering as well as in biology, psychology, economics, marketing research, artificial intelligence, and other scientific disciplines. Panos Pardalos, Series Editor.

Single Case Research Methodology

Single Case Research Methodology PDF Author: Jennifer R. Ledford
Publisher: Routledge
ISBN: 1134073712
Category : Education
Languages : en
Pages : 439

Book Description
In this anticipated new edition of Single Case Research Methodology, David L. Gast and Jennifer R. Ledford detail why and how to apply standard principles of single case research methodology to one’s own research or professional project. Using numerous and varied examples, they demonstrate how single case research can be used for research in behavioral and school psychology, special education, speech and communication sciences, language and literacy, occupational therapy, and social work. This thoroughly updated new edition features two entirely new chapters on measurement systems and controversial issues in single subject research, in addition to sample data sheets, graphic displays, and detailed guidelines for conducting visual analysis of graphic data. This book will be an important resource to student researchers, practitioners, and university faculty who are interested in answering applied research questions and objectively evaluating educational and clinical practices.

Multiple Correspondence Analysis and Related Methods

Multiple Correspondence Analysis and Related Methods PDF Author: Michael Greenacre
Publisher: CRC Press
ISBN: 1420011316
Category : Mathematics
Languages : en
Pages : 607

Book Description
As a generalization of simple correspondence analysis, multiple correspondence analysis (MCA) is a powerful technique for handling larger, more complex datasets, including the high-dimensional categorical data often encountered in the social sciences, marketing, health economics, and biomedical research. Until now, however, the literature on the su

The Handbook of Mathematical Cognition

The Handbook of Mathematical Cognition PDF Author: Jamie I.D. Campbell
Publisher: Psychology Press
ISBN: 1135423660
Category : Psychology
Languages : en
Pages : 527

Book Description
How does the brain represent number and make mathematical calculations? What underlies the development of numerical and mathematical abilities? What factors affect the learning of numerical concepts and skills? What are the biological bases of number knowledge? Do humans and other animals share similar numerical representations and processes? What underlies numerical and mathematical disabilities and disorders, and what is the prognosis for rehabilitation? These questions are the domain of mathematical cognition, the field of research concerned with the cognitive and neurological processes that underlie numerical and mathematical abilities. TheHandbook of Mathematical Cognition is a collection of 27 essays by leading researchers that provides a comprehensive review of this important research field.

Classification and Multivariate Analysis for Complex Data Structures

Classification and Multivariate Analysis for Complex Data Structures PDF Author: Bernard Fichet
Publisher: Springer Science & Business Media
ISBN: 3642133126
Category : Mathematics
Languages : en
Pages : 460

Book Description
The growing capabilities in generating and collecting data has risen an urgent need of new techniques and tools in order to analyze, classify and summarize statistical information, as well as to discover and characterize trends, and to automatically bag anomalies. This volume provides the latest advances in data analysis methods for multidimensional data which can present a complex structure: The book offers a selection of papers presented at the first Joint Meeting of the Société Francophone de Classification and the Classification and Data Analysis Group of the Italian Statistical Society. Special attention is paid to new methodological contributions from both the theoretical and the applicative point of views, in the fields of Clustering, Classification, Time Series Analysis, Multidimensional Data Analysis, Knowledge Discovery from Large Datasets, Spatial Statistics.