Data Sciences at Mason
A common thread among the sciences is the analysis of data. Within the computational sciences, the data may arise from observations of natural phenomena or from computer simulations. In either case, the task of the scientist is to extract knowledge from the data and to incorporate the new information in the corpus of extant knowledge.
In the various subareas of the computational sciences, the nature of the data and the methods for collecting and analyzing it may differ somewhat, but there are principles and techniques for understanding data that transcend the scientific subdisciplines. The Data Sciences Program of the School of Computational Sciences is concerned with methods for expanding our knowledge base in any field of science by the analysis of data.
Data sciences include traditional statistical methods, computational statistics, visualization, statistical learning, simulation, and modeling. The data sciences are firmly grounded in probability theory, logic, and other areas of mathematical analysis. Many of the methods of the data sciences are computationally-intensive. The computations are not just to "process the data" and to compute summary statistics. Rather, computations serve as a tool of discovery by providing alternative views of the data, and allowing exploration of various models suggested by these viewpoints. The Data Sciences Program is a focal point for research and graduate education in the data sciences at George Mason University. As such, it often serves in a collaborative role with other Programs in the School of Computational Sciences.
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