Quantitative Methods involves topics in both applied optimization and applied statistics. Applied optimization explores resource allocation issues that frequently arise in managerial decision making. In an era of dwindling resources and increasing competition, optimization questions have assumed a new and urgent importance. Doctoral seminars 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.
Statistics and its applications address managerial problems in which randomness or uncertainty complicates the decision environment. This specialization emphasizes in-depth study of the relevant methodology with the flexibility to apply these methods to any areas of management. Courses from departments such as economics, statistics, and industrial engineering as well as other areas of management offer the student a rich variety of topics for applied statistics 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.
Probabilistic and stochastic modeling and applications concentrate on quantifying the effects of uncertainty in managerial decision making. Stochastic models play an important role in understanding and analyzing many complex business processes. Students are encouraged to take courses from several other departments such as industrial engineering, statistics, mathematics, electrical engineering and computer sciences to strengthen the foundation of their research capabilities. Current faculty research interests in probability and stochastic modeling include inventory management, distribution, supply chain management, stochastic optimization, procurement and production planning.
- Faculty on Editorial Boards for top academic journals.
- Publications in top-tier journals by faculty and Ph.D. students.
- Doctoral fellowships available.
- Small program with low student-faculty ratio.
- Active interactions with other functional areas of the school and universities.
Student Profile (what we look for in an applicant):
- Strong analytical background.
- Fluency in speaking and writing in English.
- Work and business experience not required.
Plan of Study
Students are required to submit a formal plan of study to the Graduate School by the end of the Spring Semester of their second school year in the doctoral program, and prior to taking the preliminary examination. Selected research papers will be assigned to students in preparation for the preliminary examination. The preliminary exam will be based on the assigned papers as well as the second summer research paper.
Doctoral Dissertation Proposal/Dissertation Committee Requirement
Within twelve months after passing the preliminary examination, each student must formally present and defend a dissertation research proposal to his/her dissertation committee. To be accepted, the proposal must represent substantial progress towards completion of a doctoral thesis along with a statement of further work to be performed. Once accepted by the committee, the proposal is considered a "contract" that will guide the student towards completion of the dissertation. A student may be dropped from the program if there is a significant delay in achieving an acceptable proposal.
Defense of Dissertation
Each student is required to make a public defense of his/her dissertation. The required procedures for holding a dissertation defense are listed in the revised Ph.D. Program in Management.
Further Details on Quantitative Methods Area Program Requirements
Further information on the exact requirements of the Quantitative Methods area can be found at Quantitative Methods Area Requirements [PDF].