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Application of Mathematical Modeling in Social Science
- 1 Zengcheng Experiment middle school
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Abstract
With the promotion and application of big data, mathematical models are also more widely referenced in the research and development of different professions. In this paper, the relationship between mathematical modeling and social sciences will be explored by examining the application of mathematical modeling in social sciences through quantitative analysis. In addition, the author is willing to learn about different models related to economics, psychology, and sociology. Based on the analysis, this paper provides relevant suggestions for solving potential problems in the application of models, including, that attention should be paid to the description of contextual details, that the results of the study should take into account motivational factors, and that the data involved must be valid and not too superficial.
Keywords
social science, mathematical model, econimics, psychology, sociology, applications.
[1]. N. Gregory Mankiw: Principles of Economics,1998.
[2]. The World in the Model: How Economists Work and Think, Mary S. Morgan, 2020.
[3]. Market and Social Structure in Rural China, G. William Skinner, 2001
[4]. Dani Rodrik: Economics is Practical: If Not Misread, 2023.
[5]. Age Period Queue Model: Aggregated Data Analysis Methods, Robert M. O’Brien, 2018
[6]. A Relational Model of Data for LargeShared Data Banks, Edgar F. Codd, 1970.
[7]. Morgan (2003) Economics (Porter & Ross Cambridge History of Science Vol 7, Book Chap), Mary S. Morgan,2020.
[8]. Model based reasoning: Science, Technology, Values, Nancy J. Nersessian, 2002
[9]. Xue Zhaofeng's Lectures on Economics, Zhaofeng Xue, 2018
[10]. Piero Sraffa: The Works and Correspondence of David Ricardo. Edited with the collaboration of M.h. Dobb, 1951–73.
Cite this article
He,Y. (2024). Application of Mathematical Modeling in Social Science. Theoretical and Natural Science,55,30-33.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 2nd International Conference on Applied Physics and Mathematical Modeling
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