A comprehensive evaluation model for the quality of innovative talent cultivation in statistics in the era of big data

In order to provide quality evaluation references for innovative talents in the field of statistics in the era of big data, knowledge level, innovation ability, comprehensive literacy, and employment situation are selected as primary indicators. The analytic hierarchy process and entropy weight method are combined to evaluate the quality of innovative talent cultivation in our school's statistics major. The evaluation index system for the quality of innovative talent cultivation is determined, and a comprehensive evaluation model is constructed to quantitatively evaluate the quality of innovative talents in the field of statistics in the era of big data. The evaluation results indicate that this evaluation model is feasible and effective.