Quantitative Methods

Singapore University of Social Sciences

Quantitative Methods (BUS107)

Applications Open: 01 May 2024

Applications Close: 15 June 2024

Next Available Intake: July 2024

Course Types: Modular Undergraduate Course

Language: English

Duration: 6 months

Fees: $1391.78 View More Details on Fees

Area of Interest: Business Administration

Schemes: Alumni Continuing Education (ACE)

Funding: SkillsFuture

School/Department: School of Business

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Synopsis

BUS107 Quantitative Methods introduces management science techniques and their potential applications in various business challenges. Students will learn and practise the use of quantitative methods for various purposes, such as linear programming for optimisation problems and simulation for estimating performance measures. This course will cover linear programming, forecasting, decision analysis, simulation, and network flow problems. In addition to manual methods, this course also presents software tools for performing computing tasks. At the end of the course, students will learn how to transform data into better decisions.

Level: 1
Credit Units: 5
Presentation Pattern: Every semester

Topics

An overview of management science techniques and their applications in business operations
Linear programming models
Linear programming: A graphical solution procedure and a computer solution
Linear programming: Sensitivity analysis
Time series analysis
Forecasting methods
Decision analysis tools
Approaches to decision making with or without probabilities
Monte Carlo simulations
Discrete-event simulations
Network flow problems
Network optimisation algorithms

Learning Outcome

Apply linear programming models for optimisation problems.
Use historical data to build forecasts for future business developments.
Identify a recommended decision alternative in uncertain settings.
Interpret software output for business insights.
Demonstrate the use of a simulation model to estimate measures of performance of operational situations.
Implement iterative algorithms to find the solutions for network flow problems.