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Modern Quantification Theory
This book offers a new look at well-established quantification theory for categorical data, referred to by such names as correspondence analysis, dual scaling, optimal scaling, and homogeneity analysis. These multiple identities are a consequence of its large number of properties that allow one to analyze and visualize the strength of variable association in an optimal solution. The book contains modern quantification theory for analyzing the association between two and more categorical variables in a variety of applicative frameworks. Visualization has attracted much attention over the past decades and given rise to controversial opinions. One may consider variations of plotting systems use...
Multidimensional Nonlinear Descriptive Analysis
Quantification of categorical, or non-numerical, data is a problem that scientists face across a wide range of disciplines. Exploring data analysis in various areas of research, such as the social sciences and biology, Multidimensional Nonlinear Descriptive Analysis presents methods for analyzing categorical data that are not necessarily sampled randomly from a normal population and often involve nonlinear relations. This reference not only provides an overview of multidimensional nonlinear descriptive analysis (MUNDA) of discrete data, it also offers new results in a variety of fields. The first part of the book covers conceptual and technical preliminaries needed to understand the data ana...
Measurement, Mathematics and New Quantification Theory
The purpose of this book is to thoroughly prepare diverse areas of researchers in quantification theory. As is well known, quantification theory has attracted the attention of a countless number of researchers, some mathematically oriented and others not, but all of them are experts in their own disciplines. Quantifying non-quantitative (qualitative) data requires a variety of mathematical and statistical strategies, some of which are quite complicated. Unlike many books on quantification theory, the current book places more emphasis on preliminary requisites of mathematical tools than on details of quantification theory. As such, the book is primarily intended for readers whose specialty is outside mathematical sciences. The book was designed to offer non-mathematicians a variety of mathematical tools used in quantification theory in simple terms. Once all the preliminaries are fully discussed, quantification theory is then introduced in the last section as a simple application of those mathematical procedures fully discussed so far. The book opens up further frontiers of quantification theory as simple applications of basic mathematics.
Onomatopoeia and Relevance
This book aims to provide an account of both what and how onomatopoeia communicate by applying ideas from the relevance theoretic framework of utterance interpretation. It focuses on two main aspects of the topic: the contribution that onomatopoeia make to communication and the nature of multimodal communication. This is applied in three domains (food discourse, visual culture in Asia and translation) in the final sections of the book. It will be of interest to scholars working in the fields of pragmatics, semantics, cognitive linguistics, stylistics, philosophy of language, literature, translation, and Asian studies.
Poverty, Inequality and Growth in Developing Countries
There are many problems regarding poverty, inequality and growth in developing countries in Asia and Africa. Policy makers at the national level and at international institutions such as the United Nations, World Bank, International Monetary Fund and others have implemented various policies in order to decrease poverty and inequality. This book provides empirical observations on Asian countries and Africa. Each chapter provides theoretical and empirical analysis on regional case studies with an emphasis on policy implications. The book will be of use to many who wish to assess and improve policies in developing countries and mitigate poverty and inequality, and stimulate growth, by drawing on relevant empirical research and economic theories. Clearly, there have been numerous policy failures and the book aims to provide a basis for improving policies and outcomes based on relevant empirical observations.
Optimal Analysis of Qualitative Data with Illustrations
This is an introductory book on how to optimally analyze non-quantitative data, based on the author’s experiences over 60 years of research. The major message to the readers is that qualitative (non-quantitative) data are much more informative than quantitative data. This is good news for readers in applied areas of statistics such as those in the social sciences and marketing research, where qualitative data are everywhere. But how can one analyze qualitative data quantitatively and extract more information than from the sophisticated analysis of quantitative data? The key rests in illustrations of difficult topics in a way that anyone can understand. It is the author’s wish soon the use of AI will open a gate for simple means for optimal analysis of qualitative data, as illustrated throughout the book.
Analysis and Modeling of Complex Data in Behavioral and Social Sciences
This volume presents theoretical developments, applications and computational methods for the analysis and modeling in behavioral and social sciences where data are usually complex to explore and investigate. The challenging proposals provide a connection between statistical methodology and the social domain with particular attention to computational issues in order to effectively address complicated data analysis problems. The papers in this volume stem from contributions initially presented at the joint international meeting JCS-CLADAG held in Anacapri (Italy) where the Japanese Classification Society and the Classification and Data Analysis Group of the Italian Statistical Society had a stimulating scientific discussion and exchange.
