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BUS406Management Sciences3 Unitsintermediate

Analysis For Business Decisions

This course introduces students to fundamental aspects of Analysis for Business Decisions. It covers elements of decision analysis, decision situations, decision trees, and operational research. Students will explore system analysis, modeling, simulation, mathematical programming, transportation, assignment models, game theory, project management, inventory control, and sequencing. The course aims to equip students with the knowledge to make informed decisions in various business contexts.

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150h

Study Time

13

Weeks

12h

Per Week

intermediate

Math Level

Course Keywords

Decision AnalysisOperations ResearchMathematical ProgrammingGame TheoryInventory Control

Course Overview

Everything you need to know about this course

Course Difficulty

Intermediate Level

Builds on foundational knowledge

65%

intermediate

📊

Math Level

Moderate Math

🔬

Learning Type

Hands-on Practice

Course Topics

Key areas covered in this course

1

Decision Analysis

2

Operations Research

3

System Analysis

4

Mathematical Programming

5

Game Theory

6

Inventory Control

7

Project Management

8

Sequencing

Total Topics8 topics

Ready to Start

No specific requirements needed

This course is designed to be accessible to all students. You can start immediately without any prior knowledge or specific preparation.

Assessment Methods

How your progress will be evaluated (3 methods)

assignments

Comprehensive evaluation of course material understanding

Written Assessment

tutor-marked assessments

Comprehensive evaluation of course material understanding

Written Assessment

final examination

Comprehensive evaluation of course material understanding

Written Assessment

Career Opportunities

Explore the career paths this course opens up for you

Business Analyst

Apply your skills in this growing field

Operations Manager

Apply your skills in this growing field

Management Consultant

Apply your skills in this growing field

Project Manager

Apply your skills in this growing field

Supply Chain Analyst

Apply your skills in this growing field

Industry Applications

Real-world sectors where you can apply your knowledge

ManufacturingLogisticsFinanceHealthcareTelecommunications

Study Schedule Beta

A structured 13-week journey through the course content

Week

1

Module 1: Introduction to Decision Analysis

2h

Unit 1: Elements of Decision Analysis

2 study hours

•Define and understand the concept of a decision.
•Identify the role and skills of a decision maker.
•Explore the components of decision making: alternatives, states of nature, and criteria.
•Distinguish between states of nature and decision alternatives.

Week

2

Module 1: Introduction to Decision Analysis

2h

Unit 2: Approaches to Decision Analysis

2 study hours

•Differentiate between qualitative and quantitative approaches to decision analysis.
•Identify qualitative tools like Delphi method, market research, and historical analogy.
•Recognize quantitative tools including mathematics, probability, and statistics.
•Understand the objectives of decision making: profit maximization and loss minimization.

Week

3

Module 1: Introduction to Decision Analysis

2h

Unit 3: Types of Decision Situations

2 study hours

•Describe decision-making under certainty, uncertainty, risk, and conflict.
•Identify techniques for decision-making under each condition.
•Apply appropriate techniques to solve problems under different decision situations.
•Differentiate between the techniques used for certainty, uncertainty, and risk.

Week

4

Module 1: Introduction to Decision Analysis

2h

Unit 4: Decision Trees

2 study hours

•Describe a decision tree and its components.
•Distinguish between decision nodes and outcome nodes.
•Represent decision problems using decision trees.
•Apply fold back and tracing forward analysis.
•Calculate outcome values using the backward pass.

Week

5

Module 2: Operations Research and Modeling

2h

Unit 5: Operations Research (OR)

2 study hours

•Trace the history and development of Operations Research (OR).
•Define Operations Research and its key characteristics.
•Explain the scientific method in Operations Research.
•Discuss the necessity of Operations Research in industry.
•Outline the scope and areas of application of Operations Research.

Week

6

Module 2: Operations Research and Modeling

2h

Unit 6: Modelling In Operations Research

2 study hours

•Define a model and describe the modeling process.
•Classify different types of models: iconic, analogue, mathematical.
•Identify characteristics of good models.
•Outline the advantages and limitations of using models.
•Explain the steps involved in model construction.

Week

7

Module 2: Operations Research and Modeling

2h

Unit 7: Simulation

2 study hours

•Define simulation and its purpose.
•Outline the advantages and limitations of simulation techniques.
•Identify areas of application for simulation.
•Explain Monte Carlo simulation and its steps.
•Differentiate between deterministic and stochastic simulation.

Week

8

Module 2: Operations Research and Modeling

2h

Unit 8: Systems Analysis

2 study hours

•Define a system and discuss systems theory.
•Identify and describe the elements of a system.
•Classify different types of systems: physical, abstract, open, closed.
•Explain the concept of entropy in a system.
•Discuss the importance of systems analysis in decision-making.

Week

9

Module 3: Mathematical Programming and Optimization

2h

Unit 9: Mathematical Programming (Linear Programming)

2 study hours

•Explain the requirements and assumptions of linear programming problems.
•Identify areas of application of linear programming.
•Formulate linear programming problems from word problems.
•Discuss the advantages and limitations of linear programming.
•Solve linear programming problems using the graphical method.

Week

10

Module 3: Mathematical Programming and Optimization

2h

Unit 10: The Transportation Model

2 study hours

•Describe the nature of a transportation problem.
•Compute initial feasible solutions using the North West Corner, Least Cost, and Vogel's Approximation methods.
•Solve unbalanced transportation problems.
•Formulate a linear programming model for a transportation problem.
•Improve initial solutions using the Stepping Stone and Modified Distribution methods.

Week

11

Module 3: Mathematical Programming and Optimization

2h

Unit 11: Assignment Model

2 study hours

•Identify types of assignment problems.
•Draw a comparison between transportation and assignment problems.
•Use the Hungarian method to solve assignment problems.
•Solve maximization and minimization assignment problems.
•Handle assignment problems with restrictions.

Week

12

Module 3: Mathematical Programming and Optimization

2h

Unit 12: Project Management

2 study hours

•Define project management and its value.
•Identify the "body of knowledge areas" in project management.
•List and explain the processes involved in project management.
•Discuss the concept of project planning.
•Solve problems using PERT and CPM techniques.

Week

13

Module 4: Advanced Topics and Case Analysis

4h

Unit 13: Sequencing

2 study hours

•Explain what scheduling involves and the nature of scheduling.
•Understand the use of Gantt charts and assignment method for loading jobs in work centers.
•Discuss what sequencing involves and the use of priority rules.
•Solve simple problems on scheduling and sequencing.
•Apply Johnson's rule to sequence jobs in two machines.

Unit 14: Games Theory

2 study hours

•Define the concept of a game.
•State the assumptions of game theory.
•Describe the two-person zero-sum games.
•Explain the concept of saddle point solution in a game.
•Find pure and mixed strategies in games.

This study schedule is in beta and may not be accurate. Please use it as a guide and consult the course outline for the most accurate information.

Course PDF Material

Read the complete course material as provided by NOUN.

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Study Tips & Exam Preparation

Expert tips to help you succeed in this course

1

Review all tutor-marked assignments (TMAs) and their solutions to understand key concepts and problem-solving techniques.

2

Create concept maps linking Units 3-5 database concepts to reinforce understanding of relationships between entities and attributes.

3

Practice solving linear programming problems from Units 7-9 weekly, focusing on graphical and simplex methods.

4

Form study groups to discuss challenging topics like game theory and inventory control from Units 10-12.

5

Allocate specific time slots for revision each day in the week leading up to the exam to avoid last-minute cramming.

6

Prioritize studying units based on their weight in the final examination, as indicated in the course guide.

7

Create flashcards for key terms and formulas from each unit to aid memorization and quick recall during the exam.

8

Attempt past examination papers under timed conditions to simulate the actual exam environment and improve time management skills.

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