Abstract: The Multivariate analysis can synthesize the database and supply the direct information, so more and more anthropologists prefer the method to analyze the relationship among the different populations. Because few people tested the method, some researchers still suspected the result from the Multivariate analysis. In order to conduct Multivariate analysis on the study of anthropology, we chose adult male skulls ( n = 668) of nine populations related to the different areas. These populations included: Hebei, Inner Mongolia, Liaoning, Shaanxi, Shanxi, Xinjiang, Huabei, Yunnan and Europe. Fourteen standard linear measures were culled to do cluster and principal components analysis. The relationship and difference of the populations are very similar comparison the result from Euclidean distance coefficient and City block distance. The primary results of this study indicate that Euclidean distance coefficient is useful for primarily judging the relationship and difference of the populations. The dendragrams drew of metric data of nine populations using different cluster analysis methods were varied. It is uncertain to determine the relationship of the populations only according to the cluster dendrogram, except the results from all kinds of cluster methods are consistent. With four PCA scores methods from skull metrical data, the distributions of nine populations did not change a lot. The principal components analysis is associated with the variables. When the variables change, the component matrix and the total variance loadings change too. Compared with cluster analysis, principal components analysis is better to explain the relationship of the populations. It suggests that the conclusion from multi2variables analysis should be considered carefully.

Key words: Cluster analysis; Principle component analysis; Euclidean distance coefficient; Skull; Metric traits