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Statistics and data science aim to develop, implement, and assess methods for examining information. This information may take various forms—qualitative, quantitative, or visual—and can be gathered through diverse methods like sensors, automated systems, surveys, or randomized sampling. The driving force behind such analysis might stem from scientific inquiry, business needs, legal requirements, or policy decisions.
The Statistics and Data Science Department is committed to advancing data science, with faculty research concentrating on statistical and machine learning, computational statistics, biological computing, social statistics, and environmental metrics. Both undergraduate and graduate curricula deeply engage students in theoretical principles, practical applications, and computational techniques—the core pillars of data science.