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This book summarizes the methods and concepts of Statistical Implicative Analysis (SIA), created by Régis Gras in the 1980s to study, in a new way, the behavioural responses of French pupils to mathematics tests. Using a multidimensional, non-symmetrical data analysis method, SIA crosses a set of subjects or objects with a set of variables. It effectively complements traditional correlational and psychometric methods. SIA, through its various extensions, is today presented as a broad Artificial Intelligence method aimed at extracting trends and possible causalities in the form of rules, from a set of variables. It is based on the unlikeliness of the existence of these relationships, i.e. on the relative weakness of their counter-examples compared to what chance alone would produce. It establishes a dual topological relationship between the set of subjects and the set of variables. Many applications of this approach, driving forces or crucibles for the development of SIA, have concerned and still concern various fields such as didactics, evaluation and assessment, psychology, sociology, medicine, biology, economics, art history, and others. Key Features: Presents the foundations and representations of SIA. Provides extensions of variable sets and subjects. Includes a bonus exercise.
This book presents different data collection and representation techniques: elementary descriptive statistics, confirmatory statistics, multivariate approaches and statistical modeling. It exposes the possibility of giving more robustness to the classical methodologies of education sciences by adding a quantitative approach. The fundamentals of each approach and the reasons behind them are methodically analyzed, and both simple and advanced examples are given to demonstrate how to use them. Subsequently, this book can be used both as a course for the uninitiated and as an accompaniment for researchers who are already familiar with these concepts.
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In this 19th volume of Research on Emotion in Organizations, editors Neal M. Ashkanasy, Ronald H. Humphrey and Ashlea C. Troth orchestrate a retrospective view of the field in order to address a wide range of emotion-related topics and point to the future of research in organizational behavior and organization theory.
This volume presents recent methodological developments in data analysis and classification. It covers a wide range of topics, including methods for classification and clustering, dissimilarity analysis, consensus methods, conceptual analysis of data, and data mining and knowledge discovery in databases. The book also presents a wide variety of applications, in fields such as biology, micro-array analysis, cyber traffic, and bank fraud detection.
Statistical implicative analysis is a data analysis method created by Régis Gras almost thirty years ago which has a significant impact on a variety of areas ranging from pedagogical and psychological research to data mining. Statistical implicative analysis (SIA) provides a framework for evaluating the strength of implications; such implications are formed through common knowledge acquisition techniques in any learning process, human or artificial. This new concept has developed into a unifying methodology, and has generated a powerful convergence of thought between mathematicians, statisticians, psychologists, specialists in pedagogy and last, but not least, computer scientists specialized in data mining. This volume collects significant research contributions of several rather distinct disciplines that benefit from SIA. Contributions range from psychological and pedagogical research, bioinformatics, knowledge management, and data mining.
This book includes selecting the articles accepted for presentation and discussion at WCQR2023, held from January 25 to 27, 2023 (face to face and virtual conference). The World Conference on Qualitative Research (WCQR) is an annual event that aims to bring together researchers, academics and professionals, promoting the sharing and discussing knowledge, new perspectives, experiences and innovations in qualitative research. WCQR2023 featured four main application fields (education, health, social sciences and engineering/technology) and seven main subjects: rationale and paradigms of qualitative research; systematization of approaches with qualitative studies; qualitative and mixed methods research; data analysis types; innovative processes of qualitative data analysis; qualitative research in web context; and qualitative analysis with software support. The book is valuable for everyone interested in qualitative research, emphasizing Computer-Assisted Qualitative Data Analysis Software (CAQDAS).
This volume contains all twenty-three of the principal survey papers presented at the Symposium on Ordered Sets held at Banff, Canada from August 28 to September 12, 1981. The Symposium was supported by grants from the NATO Advanced Study Institute programme, the Natural Sciences and Engineering Research Council of Canada, the Canadian Mathematical Society Summer Research Institute programme, and the University of Calgary. tve are very grateful to these Organizations for their considerable interest and support. Over forty years ago on April 15, 1938 the first Symposium on Lattice Theory was held in Charlottesville, U.S.A. in conjunction with a meeting of the American Mathematical Society. The principal addresses on that occasion were Lattices and their applications by G. Birkhoff, On the application of structure theory to groups by O. Ore, and The representation of Boolean algebras by M. H. Stone. The texts of these addresses and three others by R. Baer, H. M. MacNeille, and K. Menger appear in the Bulletin of the American Mathematical Society, Volume 44, 1938. In those days the theory of ordered sets, and especially lattice theory was described as a "vigorous and promising younger brother of group theory." Some early workers hoped that lattice theoretic methods would lead to solutions of important problems in group theory.