Statistical Analysis of Employment Education in Colleges and Universities Based on Improved Clustering Algorithm

Abstract

In order to improve the effect of employment education in colleges and universities, this study combines the improved clustering algorithm to carry out statistical analysis of employment education in colleges and universities and analyzes the current situation of employment education in colleges and universities. In cluster analysis, considering the complexity of the distribution of statistics after the reestimation of the sample size and the possible complex correlation between the series of statistics in the group sequential design, on the premise that the statistics used will not cause type I error expansion after sample size adjustment, some rules for reestimating the sample size can be formulated. Through the simulation analysis, it can be seen that the statistical analysis system of college employment education based on the improved clustering algorithm proposed in this study has a good effect in the clustering of employment education data and has a certain role in promoting the employment of college graduates.