Application of R Programming for Bayesian Discriminant Method in Effective Teaching

The aim of this study was to explore the R programming Bayesian discriminant methods for constructing university teachers' effective teaching criterion. The record tables of 60 university teachers were carried out with the R functions. The results showed that: 1. Compared with the total score of the questionnaire, Bayesian discriminant analysis could be more effective, more accurate, and more informational. Therefore, Bayes discriminant analysis was an ideal tool for the effective teaching evaluation of university teachers. 2.Teachers with different titles could achieve effective teaching. Though professional titles represented certain teaching ability, but no high correlation was found between the two. Teachers with different titles could succeed to some extent. The promotion of teachers' teaching ability had a spiral relationship with the increase of professional titles. The paper can provide a guide for the R programming Bayesian discriminant methods in effective teaching about university teachers.