This module is not currently running in 2024 to 2025.
This module aims to provide an understanding of the importance of business and management modelling in practice and hand-on experience to apply current quantitative techniques and tools to a variety of problems encountered in business and management. Special emphasis will be given to the analysis of international case studies related to real-world business and management problems.
Indicative topics are:
• Introduction to Business Analytics
• Descriptive statistics and statistical inference.
• Probability theory and decision making under uncertainty.
• Sensitivity analysis.
• Markov processes.
• The use of statistical models in practice, such as regression, time series analysis and forecasting.
• Optimization and simulation techniques.
• Analysing complex decisions: How to determine optimal strategies in situations involving several decision alternatives.
• The applications of suitable techniques for analysing and solving business/management problems.
Total contact hours: 37
Private study hours: 113
Total study hours: 150
Main assessment methods
Individual Written Report (2000 words) (40%)
Examination, 2 hours (60%)
Albright, S.C. and Winston, W.L. (2014) Business Analytics: Data Analysis and Decision Making. (5th Ed.), Cincinnati, OH: South-Western College Publishing.
Anderson, D.R. Sweeney, D.J. Williams, T.A. and Martin, K. (2008) An Introduction to Management Science: Quantitative approaches to decision making. (12th Ed.) Cincinnati, OH: South-Western Cengage Learning
Hillier, F.S. and Hillier, M.S. (2013) Introduction to Management Science with Student CD and Risk Solver Platform Access Card: A Modeling and Cases Studies Approach with Spreadsheets. (5th Ed.), Columbus: OH: McGraw-Hill Higher Education.
See the library reading list for this module (Medway)
The intended subject specific learning outcomes.
On successfully completing the module students will be able to:
1 Demonstrate an advanced and comprehensive knowledge and understanding of core concepts and analytical frameworks in business analytics.
2 Critically apply IT to solve complex business and management problems.
3 Critically apply relevant knowledge, skills and creativity in modelling and analysing business and management problem using quantitative techniques, such as
optimization, project scheduling, network design, decision analysis and statistical models.
4 Evaluate arguments or propositions and make judgments that can guide the application of appropriate analytical approaches to complex business/management
problems.
The intended generic learning outcomes.
On successfully completing the module students will be able to:
1 Select and critically apply a variety of problem solving techniques, both autonomously and collaboratively.
2 Propose solutions to complex business/management problems.
3 Effectively communicate information, arguments and analysis in a variety of forms.
4 Work effectively as part of a group, and use self-direction, initiative and planning in the context of independent learning and the management of assignments.
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