Quantitative Methods (QM) centers on the theory and application of mathematical and statistical tools to model and analyze business problems. QM courses provide a broad introduction to data analysis, decision support models, decision analysis, simulation, and mathematical programming.

Learning the statistical and modeling tools of QM provides a competitive advantage for students specializing in any area of business, including finance, operations, marketing, accounting, and human resource management.

Undergraduate
The undergraduate core course in quantitative methods teaches students the principles of data analysis and their applications for management problems. Elective courses develop modeling skills that include optimization, decision analysis, and simulation. The models cover applications from a variety of business areas, including finance, operations, and marketing. Skills in modeling and data analysis help students obtain positions with consulting, service, and manufacturing organizations. Students are encouraged to take at least one elective course in quantitative methods to complement their courses from other departments.

            UNDERGRADUATE PROGRAM WEBSITE / TIME SCHEDULE & COURSE DESCRIPTIONS

MBA
The core courses in quantitative methods introduce students to data analysis, optimization, decision analysis, and simulation. Elective courses build on these skills with a focus on regression, forecasting, and modeling with spreadsheets. Applications in finance, operations, and marketing are emphasized. Students with skills in modeling and data analysis are prepared to assume positions with consulting, service, and manufacturing organizations.

            MBA PROGRAM WEBSITE / TIME SCHEDULE & COURSE DESCRIPTIONS

PhD
Courses in quantitative methods introduce doctoral students to the fundamentals of mathematical programming and stochastic systems. Emphasis is on theory, algorithms, and model development. These foundations are widely applicable in information systems, operations management, economics, industrial engineering, forest resources, and other areas of modeling decision making in the private and public sectors. Students are encouraged to take these courses as a complement to courses in other departments.

            PhD PROGRAM WEBSITE / TIME SCHEDULE & COURSE DESCRIPTIONS