Analytical Methods for Decision-Making
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- 12 Jul 2021
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Upon completion of this subject, the student should be able to:
- Differentiate between the nature and aspects of quantitative and qualitative methods for decision analysis
- Describe data using numerical measures and graphical methods
- Explain the basics of data collection and sampling methods
- Identify data analysis problems related to business management
- Apply relevant analytical methods to solve management problems
- 1 DESCRIPTIVE APPROACHES AND MEASURES OF DATA FOR DECISION MAKING
- 2 Measuring uncertainties in decision making – the probabilistic approach
- 3 Probability distributions – the discrete and continuous setup
- 4 Sampling methods and theorems in decision analysis
- 5 Estimations, sample comparisons and confidence intervals
- 6 Hypothesis testing for decision making
- 7 Analysis of dependencies between decision variables
- 8 Modelling decisions under risk – quantitative decision analysis
- 9 Measuring subjective data and its interpretations
- 10 Expected utility principle for decision making – concept and applications
- 11 Linear programming and decision making
- 12 Qualitative data methods and decision making
No eligibility requirements
No special requirements
This subject introduces students to both quantitative and qualitative methods and their applications to decision-making in business management. The subject covers data analysis techniques around data presentation and interpretation, estimation, sampling, hypothesis testing and regression analysis, but it also broadly discussed decision analysis and decision making under uncertainty.
Decision-making is one of the most important and challenging tasks that business managers have to do. A correct decision is hard to make without an appropriate analysis of information available. This subject introduces basic analytical methods as essential tools used to assist decision-making in business management. Some real world examples on how analytical methods can assist business managers in decision making are: making decisions under uncertainty, scenario analysis, forecasting market demand, sales revenue, profit and freight rates, monitoring product quality, and choosing the optimal combination of production inputs.
Depending on the tasks and information available, the methods vary considerably. A substantial part of this subject concerns the application of statistical methods to decision-making, but it also gravitates heavily around modern decision making techniques based on quantitative methods. You will learn how to collect, process and analyse data in order to assist decision making. You will learn a lot on decisions under risk and the techniques to rank alternatives modelled as trees, tables and lotteries.
Because this subject discusses the use of analytical tools in business management, practical applications are the main focus, and learning progress is made through practical exercises. Most exercises require calculations with the use of computers, calculators or other computational tools. Having said this, what you really need to learn are the methods rather than calculation skills.
While some may find this subject challenging, its knowledge is essential for the study of other subjects in the course, such as Transport Research Project, Warehousing and Distribution, Supply Chain Management, etc.
- Engagement Quiz (0%)
- Online Quiz (15%)
- Online Quiz (15%)
- Final Exam (40%)
- Solving tasks (%)
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