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Apr 19, 2024
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QBA 4720 - Prescriptive Analytics
Prescriptive analytics uses multiple techniques that recommend which course of action a decision maker should take within a business environment. The goal is to utilize these techniques to determine optimal strategies that can improve the results related to business decisions. In this course, students are introduced to concepts related to developing various linear and non-linear models within software tools that are commonly used by business professionals. Students apply optimization techniques to solve problems related to assignment, transportation, and network models as well as investigate other business scenarios that require additional theories such as integer and goal programing. In addition, students develop simulation models and utilize decision analysis strategies for conditions of uncertainty.
Requisites: QBA 2720 or 3710
Credit Hours: 3
Repeat/Retake Information: May be retaken two times excluding withdrawals, but only last course taken counts.
Lecture/Lab Hours: 3.0 lecture
Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I
Learning Outcomes: - Students will be able to develop payoff tables, implement decision rules, and build and analyze decision trees.
- Students will be able to apply sensitivity analysis to investigate how a model¿s output changes with respect to changes of input.
- Students will be able to create various linear and non-linear programming models within a software environment that is commonly used in business.
- Students will be able to develop optimization models that contain both hard and soft constraints with a single objective function.
- Students will be able to develop simulation models by sampling various probability distributions.
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