<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>College students’ entrepreneurship and employment have been considered an important factor in the country’s social and economic development. This paper firstly establishes a multivariate linear regression model, uses the least squares method and the great likelihood estimation method to estimate the parameters of the model, and uses the T-test and F-test to test the model. Then, we take the employment and entrepreneurship level of students in 10 colleges and universities in X urban area as an example to explore the feelings and reactions to the pressure of employment and entrepreneurship of college students and dig out the challenging factors faced by students’ employment and entrepreneurship. Finally, the regression model was used to test the influence of each factor on college students’ entrepreneurship and employment and to explore the cultivation path of college students’ employment and entrepreneurship ability enhancement. The raw mean score of college students’ employment and entrepreneurship pressure feeling is 3.046±0.418, and the explanatory strength of entrepreneurial environment and personal traits on employment and entrepreneurship intention is 43.7% and 37.7%, respectively, which indicates that personal traits and employment and entrepreneurship environment have a significant influence on college students’ employment and entrepreneurship. This study helps to promote the reform of innovation and entrepreneurship education in colleges and universities, improve the talent cultivation mechanism, and provide a positive reference value for the research on the cultivation of employment and entrepreneurship ability of college students.</p>
</abstract>

College students’ entrepreneurship and employment have been considered an important factor in the country’s social and economic development. This paper firstly establishes a multivariate linear regression model, uses the least squares method and the great likelihood estimation method to estimate the parameters of the model, and uses the T-test and F-test to test the model. Then, we take the employment and entrepreneurship level of students in 10 colleges and universities in X urban area as an example to explore the feelings and reactions to the pressure of employment and entrepreneurship of college students and dig out the challenging factors faced by students’ employment and entrepreneurship. Finally, the regression model was used to test the influence of each factor on college students’ entrepreneurship and employment and to explore the cultivation path of college students’ employment and entrepreneurship ability enhancement. The raw mean score of college students’ employment and entrepreneurship pressure feeling is 3.046±0.418, and the explanatory strength of entrepreneurial environment and personal traits on employment and entrepreneurship intention is 43.7% and 37.7%, respectively, which indicates that personal traits and employment and entrepreneurship environment have a significant influence on college students’ employment and entrepreneurship. This study helps to promote the reform of innovation and entrepreneurship education in colleges and universities, improve the talent cultivation mechanism, and provide a positive reference value for the research on the cultivation of employment and entrepreneurship ability of college students.

Challenges and Ability Enhancement of College Students’ Employment and Entrepreneurship in the Context of Big Data

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

College students’ entrepreneurship and employment have been considered an important factor in the country’s social and economic development. This paper firstly...

Challenges and Ability Enhancement of College Students’ Employment and Entrepreneurship in the Context of Big Data

Publié en ligne: 31 janv. 2024

Pages: -

Reçu: 20 déc. 2023

Accepté: 30 déc. 2023

DOI: https://doi.org/10.2478/amns-2024-0199

Mots clés
Multiple linear regression, Least squares method, Great likelihood estimation, Big data, Employment and entrepreneurship

© 2024 Wenqiu Zhai, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Challenges and Ability Enhancement of College Students’ Employment and Entrepreneurship in the Context of Big Data

Publié en ligne: 31 janv. 2024

Pages: -

Reçu: 20 déc. 2023

Accepté: 30 déc. 2023

DOI: https://doi.org/10.2478/amns-2024-0199

Mots clésMultiple linear regression, Least squares method, Great likelihood estimation, Big data, Employment and entrepreneurship

© 2024 Wenqiu Zhai, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Multiple linear regression, Least squares method, Great likelihood estimation, Big data, Employment and entrepreneurship