Construction of a Questionnaire System for College Students’ Consumption Views Based on Discrete Regression Algorithm in the Context of Ideological and Political Education
This paper constructs a questionnaire system for college students’ consumption views based on the discrete regression algorithm combined with the questionnaire method. The least squares staggered identification method is employed in the discrete regression algorithm to select the window width and re...
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Veröffentlicht in: | Applied mathematics and nonlinear sciences 2024-01, Vol.9 (1) |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | This paper constructs a questionnaire system for college students’ consumption views based on the discrete regression algorithm combined with the questionnaire method. The least squares staggered identification method is employed in the discrete regression algorithm to select the window width and reduce the integral square error of the estimation. On the basis of continuous and discrete data, the density function and regression function are estimated, and the parametric and nonparametric estimation methods are utilized to select the optimal smoothing parameters of the regression function by the method of least squares interleaved identification. In the survey of college students’ consumption outlook, the consumption outlook of college students in colleges and universities in the S province region is taken as the research object. In the questionnaire analysis, it is known that the first factor considered by college students is the sustainable use of products. The mean value of the sustainability dimension is 4.86, and the last factor considered is the ostentatiousness and extravagance of the consumption products, and the mean values are 2.65 and 2.71, respectively. Each basic situation of the college students and the social, family, personal, and influencing factors have a significant predictive effect on each dimension of the college students’ consumption outlook status. |
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ISSN: | 2444-8656 2444-8656 |
DOI: | 10.2478/amns-2024-1178 |