The method of real-time RT PCR is a laboratory technique, which achieves to quantify mRNA samples and amplify them when a small amount of sample is available. The method can be applied, among others, in gene expressions detected in tumor tissues. In this study, gene expressions identified in breast are analyzed, while the statistical analysis techniques applied are reviewed. To this end, methods for clustering gene expressions in order to reduce the number of variables under consideration are presented. Specifically, the theory of Cluster Analysis and Factor Analysis is shortly reviewed. In addition, a brief reference to the heat maps is made. Heat maps are graphical clustering techniques that group gene expressions and patients in a common graph, and present indicators of validity of the resulting clustering. Further analysis is based on Survival Analysis, which examines the evolution of the patients’ health over time. Initially, a brief overview of the theory is presented to better understand its basic concepts. Then, the time to survival is examined by applying non-parametric inference, through the Kaplan-Meier and Nelson Aalen estimators. Finally, the Cox model of proportional hazards is presented, as a semi parametric method for modeling data and the resulting residuals are examined. The above mentioned survival analysis is applied on the survival time of women and on their disease-free survival time, given that they are healthy at the starting time of the survey. Starting time is considered the day of surgery for removing the tumor. Finally, the results of these two time periods are compared and discussed.