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The choice of this topic was influenced from the concept that statistical analysis of different attributes representing certain endpoints of behavior during radio communication in cognitive networks was necessary to study the outliers occurring in those parameters. The importance of cognitive radio is explained in detail in the literature review section of this paper. The purpose of this report is to do an overview of emerging patterns in cognitive radio networks and seek an understanding of data by learning what kind of attributes that display outliers during estimation. During the course of this research, it has come to light that study of outliers require preprocessing of data during which certain anomalies of data are studied and then removed thus optimizing the dataset. In the process, two major attributes SNR and Lambda have emerged and statistically shown a pattern that helped with the estimation of outliers.