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Graph Algebra
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Graph Algebra : Mathematical Modeling With a Systems Approach

Book Details

Format Paperback / Softback
ISBN-10 1412941091
ISBN-13 9781412941099
Publisher SAGE Publications Inc
Imprint SAGE Publications Inc
Country of Manufacture GB
Country of Publication GB
Publication Date Sep 5th, 2007
Print length 104 Pages
Weight 128 grams
Dimensions 36.10 x 17.00 x 0.70 cms
Product Classification: Research methods: general
Ksh 6,650.00
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Derived from engineering literature that uses similar techniques to map electronic circuits and physical systems, graph algebra utilizes a systems approach to modelling that offers social scientists a variety of tools that are both sophisticated and easily applied.

"Brown is well known for research on mathematical modeling in the social sciences. His book introduces the graph algebra approach to modeling systems in the social sciences."

—CHOICE

Graph Algebra: Mathematical Modeling with a Systems Approach introduces a new modeling tool to students and researchers in the social sciences. Derived from engineering literature that uses similar techniques to map electronic circuits and physical systems, graph algebra utilizes a systems approach to modeling that offers social scientists a variety of tools that are both sophisticated and easily applied.

Key Features:

  • Designed for readers in the social sciences with minimal mathematical training: In this volume, the author assists readers in developing their own difference and differential equation model specifications
  • Incorporates Social Theory: This book describes an easily applied language of mathematical modeling that uses boxes and arrows to develop very sophisticated algebraic statements of social and political phenomena. Graph algebra can be used to algebraically "flesh-out" even the most complicated and sophisticated of theories.
  • Contains social science examples of graph algebra models: Social science readers can see many examples of how graph algebra can be used to model theories from a wide variety of substantive areas and disciplines. The book also describes how to estimate such models, and two examples are fully worked out.
  • Explains linear and nonlinear model specifications using graph algebra from a social science perspective: Readers can move beyond simple linear regression models by using graph algebra.

This text is ideal for use in graduate courses such as Statistical Modeling, Quantitative Methods, and Applied Mathematics.


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