In an era of dwindling resources and increasing competition, optimization questions have assumed a new and urgent importance. To that end, doctoral seminars in Quantitative Methods focus on advanced optimization applications and methodologies. Related courses are available from areas such as industrial and electrical engineering and computer sciences.
Faculty collaboration with other areas of management and related engineering programs enables students to participate in research on a stimulating range of optimization applications. Current areas of faculty interest in applied optimization include transportation, communication, distribution, and manufacturing systems. Other application domains include auditing, scheduling, and quality control.
A specialization in statistics and its applications address managerial problems in which randomness or uncertainty complicates the decision environment, offering students a rich variety of topics for research. Current faculty research interests in applied statistics include data mining, reliability theory, stochastic marketing models, auditing and acceptance sampling, statistical decision theory, and statistical quality and process control.
Most Trusted
#4
Morning Consult, 2022
Best Value School
#7
The Wall Street Journal / Times Higher Education, 2022
Most Innovative School in the U.S.
Top 10
US News and World Report, 2023
If you would like to receive more information about doctoral study in Quantitative Methods, please contact us and an Admissions Specialist will be in touch to connect you with a department representative!