Introduction To Mathematical Sociology

A comprehensive textbook on the tools of mathematical sociology and their applications Mathematical models and computer simulations of complex social systems have become everyday tools in sociology. Yet until now, students had no up-to-date textbook from which to learn these techniques. Introduction to Mathematical Sociology fills this gap, providing undergraduates with a comprehensive, self-contained primer on the mathematical tools and applications that sociologists use to understand social behavior. Phillip Bonacich and Philip Lu cover all the essential mathematics, including linear algebra, graph theory, set theory, game theory, and probability. They show how to apply these mathematical tools to demography; patterns of power, influence, and friendship in social networks; Markov chains; the evolution and stability of cooperation in human groups; chaotic and complex systems; and more. Introduction to Mathematical Sociology also features numerous exercises throughout, and is accompanied by easy-to-use Mathematica-based computer simulations that students can use to examine the effects of changing parameters on model behavior. Provides an up-to-date and self-contained introduction to mathematical sociology Explains essential mathematical tools and their applications Includes numerous exercises throughout Features easy-to-use computer simulations to help students master concepts

A comprehensive textbook on the tools of mathematical sociology and their applications Mathematical models and computer simulations of complex social systems have become everyday tools in sociology. Yet until now, students had no up-to-date textbook from which to learn these techniques. Introduction to Mathematical Sociology fills this gap, providing undergraduates with a comprehensive, self-contained primer on the mathematical tools and applications that sociologists use to understand social behavior. Phillip Bonacich and Philip Lu cover all the essential mathematics, including linear algebra, graph theory, set theory, game theory, and probability. They show how to apply these mathematical tools to demography; patterns of power, influence, and friendship in social networks; Markov chains; the evolution and stability of cooperation in human groups; chaotic and complex systems; and more. Introduction to Mathematical Sociology also features numerous exercises throughout, and is accompanied by easy-to-use Mathematica-based computer simulations that students can use to examine the effects of changing parameters on model behavior. Provides an up-to-date and self-contained introduction to mathematical sociology Explains essential mathematical tools and their applications Includes numerous exercises throughout Features easy-to-use computer simulations to help students master concepts

Until the 1960s, maths was studied as an academic subject in a desire to have more mathematicians. The current trend, however, has moved away from viewing maths as a purely intellectual endeavour and towards developing a more mathematically competent workforce and citizenry. This trend has seen a large increase in the number of maths schemes being produced by the major educational publishers, which attempt to make maths easier and more approachable by using language instead of symbols. So why do so many children still fail at maths? The author contends that to understand this, teachers need to analyze and evaluate the maths textbooks they are currently using. The author shows the reader how to systematically analyze and evaluate these textbooks. This interrogation of classroom resources, should have important implications for teaching strategies and for textbook design and use.

This is the first book by a sociologist devoted exclusively to a general sociology of mathematics. The author provides examples of different ways of thinking about mathematics sociologically. The survey of mathematical traditions covers ancient China, the Arabic-Islamic world, India, and Europe. Following the leads of classical social theorists such as Emile Durkheim, Restivo develops the idea that mathematical concepts and ideas are collective representations, and that it is mathematical communities that create mathematics, not individual mathematicians. The implications of the sociology of mathematics, and especially of pure mathematics, for a sociology of mind are also explored. In general, the author's objective is to explore, conjecture, suggest, and stimulate in order to introduce the sociological perspective on mathematics, and to broaden and deepen the still narrow, shallow path that today carries the sociology of mathematics. This book will interest specialists in the philosophy, history, and sociology of mathematics, persons interested in mathematics education, students of science and society, and people interested in current developments in the social and cultural analysis of science and mathematics.

The central topic of this book is the mathematical analysis of social systems, understood in the following rather classical way: social systems consist of social actors who interact according to specific rules of interactions; the dynamics of social systems is then the consequences of these interactions, viz., the self-organization of social systems. According to particular demands of their environment, social systems are able to behave in an adaptive manner, that is they can change their rules of interaction by certain meta rules and thus generate a meta dynamics. It is possible to model and analyse mathematically both dynamics and meta dynamics, using cellular automata and genetic algorithms. These tools allow social systems theory to be carried through as precisely as the theories of natural systems, a feat that has not previously been possible. Readership: Researchers and graduate students in the fields of theoretical sociology and social and general systems theory and other interested scientists. No specialised knowledge of mathematics and/or computer science is required.

Philosophers, social scientists, and laymen have used two perspectives in analyzing social action. One sees man's action as the result of causal forces, and the other sees action as purposive and goal directed. Mathematical treatment of social action has shown this same dichotomy. Some models of behavior describe a causal process, in which there is no place for intention or purpose. Most stochastic models of behavior, whether individual or group, are like this. Another body of work, however, employs purpose, anticipation of some future state, and action designed to maximize the proximity to some goal. Classical microeconomic theory, statistical decision theory, and game theory exemplify this direction.This book examines these two directions of work, and makes original contributions to the second. An introductory chapter outlines these two bodies of work, and casts them in a common frame, to display their similarities and differences. Chapter 2 reviews at length recent work in stochastic processes that makes up the first body of work, which sees social action as the resultant of causal forces. The remaining chapters develop a mathematical framework for the study of systems of social action using a purposive theoretical base. These chapters are designed particularly to contribute to the study of collective decisions, a form of social action that has proved particularly challenging to theoretical analysis. First published in 1973, this became a significant work both in problem solving and in the future career of the author. It is of continuing importance to researchers and students interested in statistical analysis.