The area of Quantitative Methods is dedicated to excellent research and outstanding teaching in the Mitchell E. Daniels, Jr. School of Business undergraduate and graduate programs.
The Quantitative Methods area offers courses covering topics on various quantitative methods and tools for managerial decision-making, such as business statistics, management science, predictive analysis, six sigma and quality management, data mining, spreadsheet modeling, optimization, simulation, and others. The students in our programs have opportunities to participate in inter-collegiate case competitions, experiential learning initiatives, and student-led club activities. U.S. News & World Report has consistently ranked the Mitchell E. Daniels, Jr. School of Business undergraduate program in the quantitative methods/analysis specialty among the top programs along with MIT, Columbia, Carnegie Mellon, University of Pennsylvania, UC Berkeley, and other peer institutions having a strong STEM (Science, Technology, Engineering, and Mathematics) focus.
The research interests of Quantitative Methods faculty are broad and interdisciplinary, involving topics in multivariate statistical analysis, statistical quality control and improvement, reliability analysis, network science, machine learning, data mining, information theory, big data technologies, game theory, contract and negotiation analysis, combinatorial optimization, integer programming, nonlinear mixed-integer optimization, polyhedral theory, complexity and approximation, symbolic computing, etc. The Quantitative Methods faculty have been well recognized for their research achievements. They have prolifically published research work in the top economics, management, engineering, statistics, and applied mathematics journals and conference proceedings. The area’s faculty have received prestigious awards and prizes in teaching and research from the Daniels School, Purdue University, national science foundation, and international academic associations.
