In practical applications, qualitative data often have problems with missing data values and inconsistency, which affects the accuracy of the analysis results. How to deal with missing values in data and how to choose appropriate interpolation methods are still a challenge. To this end, this paper proposes a qualitative indicator report analysis based on SAS software statistical technology. This study first outlines the specific meaning of qualitative indicators, then studies the operation steps, common methods, and encoding and conversion of qualitative data for data import and cleaning in SAS software. Then, this study uses the PROC FREQ module in the software to perform descriptive analysis of qualitative indicators and output and interpretation of frequency tables. At the same time, this study also uses the Chi-Square Test to test the independence of qualitative indicators, and gives the Chi-Square test syntax, Chi-Square value and p-value explanation and specific functions. Finally, this paper conducts an experimental study on the relationship between gender, smoking habits, education level and health status as a specific case. The experimental research results show that the chi-square value of BMI (Body Mass Index) and smoking habits is 6.42, and the P value is 0.011, indicating that there is a significant correlation between BMI level and smoking behavior.