In this paper, we proposed the analysis of emotional profiles using statistical features. By organizing the staged Fisher's space model, the analysis improves the separation on the Fisher's feature space with high complexity. The staged Fisher's space is achieved by the successive combining of binary Fisher's space model, which has simple structure and high performance. On each stage, it forms Fisher's linear discriminant according to the two groups which contain each emotion class, and generates the binary Fisher's space model.