Quality assessment of intelligent physical education teaching in universities based on multivariate statistical analysis and regression analysis

In this paper, we first propose the basic technical support and service and management of university intelligent physical education composition, and on this basis, we propose a teaching quality assessment model based on multivariate statistical analysis and regression analysis. Among them, multivariate statistical analysis is used to calculate the factor loadings A of physical education teaching, and multiple linear regression is used to establish the teaching quality assessment model and test it. Finally, an empirical analysis of teaching quality assessment was conducted with smart physical education as an example. The results show that the comprehensive assessment value of smart physical education teaching quality based on a multiple linear regression model is very close to the actual value, and the error value ranges from [0.003 to 0.027]. The error values are smaller than [0.0135~0.0921] of the ANN model and [0.0635~0.1033] of the neural network model. The research in this paper can provide scientific quality assessment methods and theoretical support for smart physical education in colleges and universities to promote the development of smart physical education and improve teaching quality in colleges and universities.