MSBA 757: Prescriptive Analytics Master Syllabus
Course Instructor:
Office Number:
Office Hours:
Email:
Course Meeting Times:
Required Course Materials:
- Required Text: Taylor III, B.W., Introduction to Management Science, Latest Edition, Pearson Education.
- Required Software: Excel Solver, LINGO, Crystal Ball (optional)
Course Website: Yes
Course Description
This is a course in applied operations research for business management. Business situations are represented by analytical mathematical models solved by the effective application of the methods mathematical programming and probabilistic process analysis. Emphasis is placed on the proper association of a specific methodology with a particular type of business problem. Specific topics include linear programming. integer programming, binary programming, transportation and transshipment problems, assignment problems, network flow models, decision theory, queuing models, and Monte Carlo simulation. Emphasis is placed on the effective written communication of technical data and results. Extensive use is made of computer software in problem solving.
Program Goals
Our graduates will acquire essential knowledge and be competent in:
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Ethical Decision Making: Understand, apply, and evaluate ethical data practices when collecting, analyzing and sharing data to improve the decision-making process in business.
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Fundamental Analytics Techniques and Skills: Demonstrate an in-depth understanding of the most commonly used analytics techniques.
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Identification and Application of Analytics: Apply analytics to different functional areas of business and assess its impact.
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Collaboration and Communication Skills: Effectively interact with clients and communicate data-driven insights to them.
Learning Objectives
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To foster critical thinking and independent problem solving skills.
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To develop the skill to mathematically model business problems and to identify the appropriate analysis methodology for their technical solution.
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Acquire competence with some of the software used in practice by professional to facilitate decision making.
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To develop the skills to communicate and present technical data, model results, and analysis.
Student Responsibilities
Students are expected to attend all scheduled classes. Class participation includes questions and answers, as well as presentation of solved homework problems. The student is solely responsible for all assignments and material presented in class. Mastery of the subject matter in this course is measured by skill and proficiency in problem solving. Proficiency is gained by practice. The assigned homework should be regarded as the minimum amount of practice required. It is in the best interest of the student to complete each and every homework assignment. Homework is for the student’s benefit; it is a diagnostic tool by which the student may assess their understanding and performance. Failure to do so will adversely affect performance, and will negatively impact exam and course grades. The student is cautioned to avoid falling behind. Problems for each topic in the syllabus will be assigned from the corresponding chapter in the text. Some assignments may be collected, as announced. The student is responsible for completing on time each and every required assignment, including exams and reports.
Methods of Student Evaluation
Mastery of the subject matter in this course is measured by skill and proficiency in problem solving. Course grades are objectively based on the examinations (up to four) that are given and on the assigned professional reports/presentations that are required to be submitted. The exams consist of multiple word problems describing business situations to be modeled and solved. All graded work is solely individual effort.
| Proposed Course Schedule (Some minor adjustments may occur) | |
|---|---|
| Week 1 | Introduction and Course Overview to Management Science |
| Week 2 | Linear Programming: Model Formulation and Sensitivity Analysis |
| Week 3 | Linear Programming: Multivariate Modeing and Computer Solution |
| Week 4 | Integer and Binary Programming |
| Week 5 | Transportation and Related Problems |
| Week 6 | Decision Theory |
| Week 7 | Queuing Analysis |
| Week 8 | Simulation |
| Final | University Scheduled Exam Time |
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