Qualitative Mathematics For The Social Sciences

This book combines psychological and mathematical perspectives to analyse how qualitative mathematics can be used to create models of social and psychological processes.

In this book Lee Rudolph brings together international contributors who combine psychological and mathematical perspectives to analyse how qualitative mathematics can be used to create models of social and psychological processes. Bridging the gap between the fields with an imaginative and stimulating collection of contributed chapters, the volume updates the current research on the subject, which until now has been rather limited, focussing largely on the use of statistics. Qualitative Mathematics for the Social Sciences contains a variety of useful illustrative figures, introducing readers from the social sciences to the rich contribution that modern mathematics has made to our knowledge of logic, structures, and dynamic systems. A beguiling array of conceptual systems, topological models and fractals are discussed which transcend the application of statistics, and bring a fresh perspective to the study of social representations. The wide selection of qualitative mathematical methodologies discussed in this volume will be hugely valuable to higher-level undergraduate and postgraduate students of psychology, sociology and mathematics. It will also be useful for researchers, academics and professionals from the social sciences who want a firmer grasp on the use of qualitative mathematics.

Introducing eight analytical approaches that are key to successful social science research, this book helps you get to grips with theory and apply it to qualitative analysis. With two ‘matched chapters’ dedicated to each approach, it provides a balance between theory and analytical method. The first chapter grounds the approach in theory and the second uses real-world examples to show how to conduct your own analysis using the approach. Drawing on the contributing authors’ wealth of experience, the book: · Highlights how analysis relates to the entire research process and helps you position your analysis within the larger context of your research · Provides a strong, theoretical foundation for building good qualitative analysis · Guides you through translating theory into real-world practice in your own research Detailed, clear and accessible, this book is perfect for students who want to understand the theory behind qualitative analysis before conducting their own research, or develop their understanding of specific approaches.

This edited volume presents examples of social science research projects that employ new methods of quantitative analysis and mathematical modeling of social processes. This book presents the fascinating areas of empirical and theoretical investigations that use formal mathematics in a way that is accessible for individuals lacking extensive expertise but still desiring to expand their scope of research methodology and add to their data analysis toolbox. Mathematical Modeling of Social Relationships professes how mathematical modeling can help us understand the fundamental, compelling, and yet sometimes complicated concepts that arise in the social sciences. This volume will appeal to upper-level students and researchers in a broad area of fields within the social sciences, as well as the disciplines of social psychology, complex systems, and applied mathematics.

This book presents a broad spectrum of problems related to statistics, mathematics, teaching, social science, and economics as well as a range of tools and techniques that can be used to solve these problems. It is the result of a scientific collaboration between experts in the field of economic and social systems from the University of Defence in Brno (Czech Republic), G. d’Annunzio University of Chieti-Pescara (Italy), Pablo de Olavid eUniversity of Sevilla (Spain), and Ovidius University in Constanţa, (Romania). The studies included were selected using a peer-review process and reflect heterogeneity and complexity of economic and social phenomena. They and present interesting empirical research from around the globe and from several research fields, such as statistics, decision making, mathematics, complexity, psychology, sociology and economics. The volume is divided into two parts. The first part, “Recent trends in mathematical and statistical models for economic and social sciences”, collects papers on quantitative matters, which propose mathematical and statistical models for social sciences, economics, finance, and business administration. The second part, “Recent trends in qualitative theories for economic and social sciences”, includes papers on qualitative matters, which discuss social, economic, and teaching issues. It is an ideal reference work for all those researchers interested in recent quantitative and qualitative tools. Covering a wide range of topics, it appeals in equal measure to mathematicians, statisticians, sociologists, philosophers, and specialists in the fields of communication, social and political sciences.

"Princeton University Press published Imai's textbook, Quantitative Social Science: An Introduction, an introduction to quantitative methods and data science for upper level undergrads and graduates in professional programs, in February 2017. What is distinct about the book is how it leads students through a series of applied examples of statistical methods, drawing on real examples from social science research. The original book was prepared with the statistical software R, which is freely available online and has gained in popularity in recent years. But many existing courses in statistics and data sciences, particularly in some subject areas like sociology and law, use STATA, another general purpose package that has been the market leader since the 1980s. We've had several requests for STATA versions of the text as many programs use it by default. This is a "translation" of the original text, keeping all the current pedagogical text but inserting the necessary code and outputs from STATA in their place"--

The main purpose of this book is not only to present recent studies and advances in the field of social science research, but also to stimulate discussion on related practical issues concerning statistics, mathematics, and economics. Accordingly, a broad range of tools and techniques that can be used to solve problems on these topics are presented in detail in this book, which offers an ideal reference work for all researchers interested in effective quantitative and qualitative tools. The content is divided into three major sections. The first, which is titled “Social work”, collects papers on problems related to the social sciences, e.g. social cohesion, health, and digital technologies. Papers in the second part, “Education and teaching issues,” address qualitative aspects, education, learning, violence, diversity, disability, and ageing, while the book’s final part, “Recent trends in qualitative and quantitative models for socio-economic systems and social work”, features contributions on both qualitative and quantitative issues. The book is based on a scientific collaboration, in the social sciences, mathematics, statistics, and economics, among experts from the “Pablo de Olavide” University of Seville (Spain), the “University of Defence” of Brno (Czech Republic), the “G. D’Annunzio” University of Chieti-Pescara (Italy) and “Alexandru Ioan Cuza University” of Iaşi (Romania). The contributions, which have been selected using a peer-review process, examine a wide variety of topics related to the social sciences in general, while also highlighting new and intriguing empirical research conducted in various countries. Given its scope, the book will appeal, in equal measure, to sociologists, mathematicians, statisticians and philosophers, and more generally to scholars and specialists in related fields.

Written for social science students who will be working with or conducting research, Mathematics for Social Scientists offers a non-intimidating approach to learning or reviewing math skills essential in quantitative research methods. The text is designed to build students’ confidence by presenting material in a conversational tone and using a wealth of clear and applied examples. Author Jonathan Kropko argues that mastering these concepts will break students’ reliance on using basic models in statistical software, allowing them to engage with research data beyond simple software calculations.