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

<p>In this paper, the principles, algorithms and different linear regression models are sorted out and finalized to determine the multiple linear regression model suitable for this study. The different types of regression are synthesized through the elastic net algorithm. Based on the multiple linear regression model, students’ performance in language, mathematics and English was used as the dependent variable Y on behalf of academic performance, and five sports such as physical education and hygiene were used as the independent variable X, to carry out an empirical study on 3,800 students. From this, it was concluded that the contribution rates affecting language achievement were sports attitude, environment, and hygiene in the order of coefficients of 0.548, 0.312, and −0.266. In contrast, exercise habit [B=−0.032, t=−1.574, P=0.116] and sports knowledge [B=0.027, t=1.561, P=0.119] did not pass the test of significance. The contribution of influencing math achievement was in the order of sports environment and attitude with coefficients of 0.402 and 0.327, which were positively correlated with math achievement Y2. The contribution rate affecting English achievement is in the order of sports hygiene, sports attitude and exercise habit, and their coefficients are 0.398, 0.295 and 0.124, all of which are positively correlated with English achievement Y3.</p>
</abstract>

In this paper, the principles, algorithms and different linear regression models are sorted out and finalized to determine the multiple linear regression model suitable for this study. The different types of regression are synthesized through the elastic net algorithm. Based on the multiple linear regression model, students’ performance in language, mathematics and English was used as the dependent variable Y on behalf of academic performance, and five sports such as physical education and hygiene were used as the independent variable X, to carry out an empirical study on 3,800 students. From this, it was concluded that the contribution rates affecting language achievement were sports attitude, environment, and hygiene in the order of coefficients of 0.548, 0.312, and −0.266. In contrast, exercise habit [B=−0.032, t=−1.574, P=0.116] and sports knowledge [B=0.027, t=1.561, P=0.119] did not pass the test of significance. The contribution of influencing math achievement was in the order of sports environment and attitude with coefficients of 0.402 and 0.327, which were positively correlated with math achievement Y2. The contribution rate affecting English achievement is in the order of sports hygiene, sports attitude and exercise habit, and their coefficients are 0.398, 0.295 and 0.124, all of which are positively correlated with English achievement Y3.

Linear regression analysis of the correlation between students’ physical education performance and academic achievement in the context of smart physical education in colleges and universities

Applied Mathematics and Nonlinear Sciences

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

In this paper, the principles, algorithms and different linear regression models are sorted out and finalized to determine the multiple linear regression model...

Linear regression analysis of the correlation between students’ physical education performance and academic achievement in the context of smart physical education in colleges and universities

Publié en ligne: 26 févr. 2024

Pages: -

Reçu: 15 janv. 2024

Accepté: 22 janv. 2024

DOI: https://doi.org/10.2478/amns-2024-0641

Mots clés
Elastic net algorithm, Academic achievement, Linear regression, Contribution rate

© 2023 Jin Chen, published by Sciendo

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

Linear regression analysis of the correlation between students’ physical education performance and academic achievement in the context of smart physical education in colleges and universities

Publié en ligne: 26 févr. 2024

Pages: -

Reçu: 15 janv. 2024

Accepté: 22 janv. 2024

DOI: https://doi.org/10.2478/amns-2024-0641

Mots clésElastic net algorithm, Academic achievement, Linear regression, Contribution rate

© 2023 Jin Chen, published by Sciendo

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

Mots clés
Elastic net algorithm, Academic achievement, Linear regression, Contribution rate