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The Factor Analysis of University English Examination Results Based on the Multilevel Model

Shaoyun Long1,*, Qianying Long2

1 Foreign languages college, Jiangxi Normal University Jiangxi, China 330022
2 College of Tourism and Service Management, Nankai University Tianjin, China 300350
Address: no. 99, Ziyang avenue, Nanchang City, Jiangxi province

* Corresponding Author: Shaoyun Long, email

Intelligent Automation & Soft Computing 2020, 26(3), 585-595. https://doi.org/10.32604/iasc.2020.013937

Abstract

The traditional factor analysis models, such as the generalized linear regression model and the gistic regression model have disadvantages of large standard error of analysis results. For this purpose, a multilevel factor analysis model based on time series and independent variable data is designed. The OLS estimation analysis method is used to establish the basic environment form, to derive the model calculation parameters and to complete the environment construction of the multilevel analysis model. On the basis of the construction environment, the double-level environment reference module and the multilevel factor analysis module are designed to realize the design of the multi water leveling factor analysis model. Compared with the traditional factor analysis model, the standard error of the analysis results are reduced by 15%.

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APA Style
Long, S., Long, Q. (2020). The factor analysis of university english examination results based on the multilevel model. Intelligent Automation & Soft Computing, 26(3), 585-595. https://doi.org/10.32604/iasc.2020.013937
Vancouver Style
Long S, Long Q. The factor analysis of university english examination results based on the multilevel model. Intell Automat Soft Comput . 2020;26(3):585-595 https://doi.org/10.32604/iasc.2020.013937
IEEE Style
S. Long and Q. Long, “The Factor Analysis of University English Examination Results Based on the Multilevel Model,” Intell. Automat. Soft Comput. , vol. 26, no. 3, pp. 585-595, 2020. https://doi.org/10.32604/iasc.2020.013937



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This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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