In this paper, we present a selection method of power traces to improve the efficiency of power analysis attacks. The proposed method improves the correlation factor by biasing distribution of power traces. The biasing is to select a subset from many traces. We demonstrate our method through correlation power analysis (CPA) experiments using two different devices. The results clearly show that the selection of power traces has a significant impact on the results of CPAs. Based on the selection method, an evaluation method to detect such biasing in power traces is also proposed. The method can be used to achieve fair comparison of statistical distinguishers for power analysis attacks.