DCSN205 - Managerial Decision Making: Difference between revisions
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|Number=DCSN205 | |Number=DCSN205 | ||
|Credits=3 | |Credits=3 | ||
|Has_subject=Decision System | |||
|Taught_at=Olayan School of Business | |Taught_at=Olayan School of Business | ||
}} | }} | ||
{{Course | {{Course | ||
|Description=This course is a spreadsheet-based introduction to the tools and techniques of modern managerial decision making. It addresses formulation of models that can be used to analyze complex problems taken from various functional areas of management, including finance, marketing, operations, and human resources. The goal is to understand how business decisions are reached, what tradeoffs are made, and how outcomes depend on the underlying data. A broad range of analytical methods is covered, including linear programming, integer linear programming, non-linear programming, multi-objective decision analysis, decision trees, queuing and service models, and Monte Carlo simulation. Software packages like Excel, Tree Plan, and Crystal Ball will be used. | |Description=This course is a spreadsheet-based introduction to the tools and techniques of modern managerial decision making. It addresses formulation of models that can be used to analyze complex problems taken from various functional areas of management, including finance, marketing, operations, and human resources. The goal is to understand how business decisions are reached, what tradeoffs are made, and how outcomes depend on the underlying data. A broad range of analytical methods is covered, including linear programming, integer linear programming, non-linear programming, multi-objective decision analysis, decision trees, queuing and service models, and Monte Carlo simulation. Software packages like Excel, Tree Plan, and Crystal Ball will be used. | ||
|Topics=Making Decisions Using Models, Overview of Optimization, Linear Programming, Sensitivity Analysis, Network Flow Models, Integer Programming, Optimization with Multiple Objectives, Nonlinear Optimization | |Topics=Making Decisions Using Models, Overview of Optimization, Linear Programming, Sensitivity Analysis, Network Flow Models, Integer Programming, Optimization with Multiple Objectives, Nonlinear Optimization, Project Management Models, Queueing Models, Simulation | ||
|LearningGoals=DCSN205_B-LG1: Business professional knowledge and competence, DCSN205_B-LG2: Decision making | |LearningGoals=DCSN205_B-LG1: Business professional knowledge and competence, DCSN205_B-LG2: Decision making | ||
|SpecificLearningObjectives=DCSN205_B-LG1.1: Business professional knowledge and competence, DCSN205_B-LG2.1: Decision making | |SpecificLearningObjectives=DCSN205_B-LG1.1: Business professional knowledge and competence, DCSN205_B-LG2.1: Decision making | ||
|PrerequisiteCourses=MATH 204 - Math for Social Sciences II, | |PrerequisiteCourses=MATH 204 - Math for Social Sciences II, CMPS209 - Computers and Programming for the Sciences | ||
|OptionalCorequisiteCourses=DCSN200 - Operations Management, | |OptionalCorequisiteCourses=DCSN200 - Operations Management, | ||
|InstructionalMethodology=Lecture, Class Discussion, Assignment, Quiz | |InstructionalMethodology=Lecture, Class Discussion, Assignment, Quiz | ||
|PerformanceEvaluation=DCSN205_Midterm Exam, DCSN205_Final Exam, DCSN205_Lab Test, DCSN205_Assignments Quizzes Attendance and Participation | |PerformanceEvaluation=DCSN205_Midterm Exam, DCSN205_Final Exam, DCSN205_Lab Test, DCSN205_Assignments Quizzes Attendance and Participation | ||
Latest revision as of 11:16, 10 February 2014
| DCSN205 - Managerial Decision Making | |
|---|---|
| Course Number | DCSN205 |
| Number of Credit Hours | 3 |
| Course Subject | Decision System |
| Taught at | Olayan School of Business |
Course Description
This course is a spreadsheet-based introduction to the tools and techniques of modern managerial decision making. It addresses formulation of models that can be used to analyze complex problems taken from various functional areas of management, including finance, marketing, operations, and human resources. The goal is to understand how business decisions are reached, what tradeoffs are made, and how outcomes depend on the underlying data. A broad range of analytical methods is covered, including linear programming, integer linear programming, non-linear programming, multi-objective decision analysis, decision trees, queuing and service models, and Monte Carlo simulation. Software packages like Excel, Tree Plan, and Crystal Ball will be used.
Topical Coverage
Making Decisions Using Models, Overview of Optimization, Linear Programming, Sensitivity Analysis, Network Flow Models, Integer Programming, Optimization with Multiple Objectives, Nonlinear Optimization, Project Management Models, Queueing Models, Simulation
Learning Goals
DCSN205_B-LG1: Business professional knowledge and competence, DCSN205_B-LG2: Decision making
Specific Learning Objectives
DCSN205_B-LG1.1: Business professional knowledge and competence, DCSN205_B-LG2.1: Decision making
Prerequisite Courses
MATH 204 - Math for Social Sciences II, CMPS209 - Computers and Programming for the Sciences
Required Academic Standing
Corequisite Courses
Optional Prerequisite Courses
Optional Corequisite Courses
DCSN200 - Operations Management
Instructional Methodology
Lecture, Class Discussion, Assignment, Quiz
Performance Evaluation
DCSN205_Midterm Exam, DCSN205_Final Exam, DCSN205_Lab Test, DCSN205_Assignments Quizzes Attendance and Participation