Theoretical and Natural Science
- The Open Access Proceedings Series for Conferences
Theoretical and Natural Science
Vol. 39, 21 June 2024
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Study on the influencing factors of the STR based on linear regression-take China as example
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Abstract
In recent years, the student-teacher ratio (STR) has received widespread attention in the field of education. By now, the STR has become an important indicator of education. This article first theoretically analyzes the relationship between the STR and the proportion of the school-age population in the middle school stage to the total population of the country, teacher gender ratio, the proportion of education expenditure in GDP, and GDP per capita, predicting that there is a positive correlation between STR and the proportion of school-age population in the total population, and there is a negative correlation between STR and the rate of women teacher, the proportion of education funds in GDP, and GDP per capita. Then this article establishes the regression equation of STR and the above variables through the data of secondary schools in China in the past 30 years. And it finds that there is a positive correlation between STR and the proportion of the school-age population in the middle school stage to the total population of the country, and there is a negative correlation between STR and the rate of women teachers, and GDP per capita, and there is no linear relation between STR and the proportion of education funds in GDP. Also, this article finds that proportion of the proportion of the school-age population in the middle school stage to the total population of the country, rate of women teachers and GDP per capita have collinearity relationship.
Keywords
Student-teacher ratio, influencing factors, linear regression
References
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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 Mathematical Physics and Computational Simulation
- ISBN (Print)
- 978-1-83558-463-7
- ISBN (Online)
- 978-1-83558-464-4
- Published Date
- 21 June 2024
- Series
- Theoretical and Natural Science
- ISSN (Print)
- 2753-8818
- ISSN (Online)
- 2753-8826
- DOI
- 10.54254/2753-8818/39/20240563
- Copyright
- 21 June 2024
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited