In this paper, we discuss problems encountered in analyzing high dimensional data and propose possible solutions. We first recognize the increased importance of the second order statistics in analyzing high dimensional data and the shortcoming of the minimum distance classifier in high dimensional data. By investigating characteristics of high dimensional data, we suggest the reson why the second order statistics must be taken into account in high dimensional data. Recognizing the importance of the second order statistics, there is a need to represent the second order statistics effectively. However, as the data dimensionality increases, it becomes more difficult to perceive and compare information present in statistics derived from data. In order to overcome such a problem, we propose a method to visualize statistics using color code. By representing statistics using a color code, one can more easily compare the first and the second statistics.