1. Multiple choice research: Multiple choice analysis can be divided into four types, including multiple choice, single choice-multiple choice, multiple choice-single choice and multiple choice-multiple choice.
2. Cluster analysis: Cluster analysis classifies sample objects based on multiple research titles. If clustering is based on samples, the system will automatically identify whether to use K-means clustering algorithm or K-prototype clustering algorithm by using the "clustering" function in the advanced method module of SPSSAU.
3. Weight research: Weight research is used to analyze the importance of various factors or indicators in the comprehensive system and finally build a weight system. There are many methods to study the weight, including factor analysis, entropy method, AHP analytic hierarchy process, TOPSIS method, fuzzy comprehensive evaluation method, grey correlation method and so on.
This concludes the introduction of data analysis methods in this paper.