| Summary: | In this paper, observations and data analysis of multiple impact variables are performed by cluster analysis algorithm, and data sets are set up using statistical analysis methods to calculate similarity measures to obtain weight values. The evaluation indexes are categorized to constrain index data analysis, and the outlier degree of this data object is calculated based on the attribute value weights. Factor scores were obtained for each sample in the evaluation index data set by the statistical analysis method to derive the optimal automated evaluation model. The results show that the indicators of the satisfaction evaluation system are all 60% and above, and the highest indicator of teachers’ love and dedication is 90% and the statistical analysis method can build a teacher ethics evaluation index system that meets the actual needs.
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