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The MS in quantitative methods and modeling (QMM) is a 30-credit program.  The QMM program is designed to provide a broad spectrum of basic quantitative skills; thus, the required specialization courses span the areas of operations research, statistics, and computer information systems.  The flexible elective requirements permit the creation of a five-course quantitative sequence tailored to a student's professional and/or educational objectives.  Students also have the option of doing a graduate internship.  The list of preliminary and specialization courses is given below. 

 

Preliminary Courses                 (7.5 - 9 credits)

Students with an appropriate background will be able to reduce the number of credits in preliminary requirements. Grades in 8000-level courses are not calculated in the grade point average. English language modules offered by the Division of Continuing and Professional Studies are required for non-native English speakers, and may be waived based on a waiver exam.

 

Calculus for Applications I*3 credits
Financial Accounting3 credits
or 
Fundamentals of Microeconomics1.5 credits
Applied Statistical Analysis for Business Decisions3 credits


Courses in Specialization             (30 credits)

Required                                       (16.5 credits)  
Information Systems for Managers I1.5 credits
Principles of Database Management Systems3 credits
Introduction to Quantitative Modeling3 credits
Simulation Modeling and Analysis3 credits
Regression and Forecasting Models for Business Applications3 credits
Basic Software Tools for Data Analysis 

(

)

3 credits

Electives             (13.5 credits)

Five courses to be selected with approval of the department advisor. It is recommended that the student select at least one course in each of the three areas: OPR, STA, and CIS. A maximum of three courses may be selected from any one area. Students may select

or an approved quantitatively oriented course offered outside the department.

*Students may substitute MTH 2207 Applied Calculus and Matrix Applications on a space-available basis.

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