A Research on the Application of Multi-Objective Stratified Isometric Composite Sampling

Based on the survey data of 8 indicators of 800 urban households consumption expenditures in 12 cities and counties which are not provincial capitals, multi-objective stratified systematic compound sampling method is verified. In the first stage, Q-Hierarchical cluster analysis method is adopted; the sample distance is calculated with the Squared Euclidean distance, and the minority class distance is calculated with the Between-groups linkage method. The results show that under the condition of the same sample size, the errors between sample mean and population mean of multi-objective stratified sampling method are smaller than that of random sampling. In the second stage, random start symmetric systematic sampling is adopted based on the hierarchical clustering. The results show that under the same sample conditions, when sampling for multi-objective, stratified systematic compound sampling is better than random sampling, and can decrease the sampling errors significantly.