College students' innovation and entrepreneurship model based on probability theory statistics
In order to better realize the innovation and entrepreneurship model of college students, the author proposed a statistical method based on probability theory. Based on the data obtained from the questionnaire on "university students in the community of innovation and entrepreneurship", th...
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Veröffentlicht in: | Applied mathematics and nonlinear sciences 2023-07, Vol.8 (2), p.1601-1610 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | In order to better realize the innovation and entrepreneurship model of college students, the author proposed a statistical method based on probability theory. Based on the data obtained from the questionnaire on "university students in the community of innovation and entrepreneurship", this paper analyzes the existing problems already in the innovation and entrepreneurship of college students in the community. Second, on the basis of pattern analysis and data reliability, the analysis method based on principal analysis is used to determine the eight factors that influence the innovation and entrepreneurship among college students in the community. In addition, innovative and effective business opportunities for community college students based on statistical results have been developed. The test results show that: from the prediction of the last three sets of models, the average relative error of y1 and y2 is 0.0013 and 0.0984 respectively, and the error is less 0.1, indicating that the relative error of the model is within the acceptable range. The results calculated by the model are accurate according to the actual situation from the question. It can be seen that the author uses the analysis method as the principal analysis to determine the eight important factors that affect the innovation and entrepreneurship of the students. High society is necessary, which proves that the design model created by the author is scientific and practical. |
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ISSN: | 2444-8656 2444-8656 |
DOI: | 10.2478/amns.2023.1.00121 |