Decision Analytics (BUST10133)
Normal Year Taken
Delivery Session Year
Visiting students must have at least 4 Business courses at grade B or above. This MUST INCLUDE at least one Finance course at intermediate level. We will only consider University/College level courses.
This course provides students with an understanding of the techniques available for the analysis of management problems in which uncertainty plays a significant role.
The techniques used for the analysis of management problems are illustrated using examples based on applications from the areas of capacity planning, quality control, consumer behaviour, inventory management, finance and purchasing. SYLLABUS: The course is comprised of four modules which cover four modelling techniques: 1. Markov Chains 2. Markov Decision Processes 3. Decision Analysis 4. Sequential Sampling. STUDENT LEARNING EXPERIENCE: 1. Lectures explain the concepts underpinning four modelling techniques for management problems involving uncertainty and present a series of illustrative examples. Lectures are supported by suggested readings from the recommended texts. Students are advised to attend all lectures. 2. Students gain further experience in the application of the techniques to management problems by working through the example questions uploaded in the 'Tutorials' folder on Learn at their own pace, with feedback via online solutions. 3. Optional example class tutorials summarise each topic covered by reviewing a past examination question. 4. Additional web-based material provides students with feedback as they tackle further past examination questions. 5. The coursework project requires students to build a model of a management case study, to analyse the model using techniques covered in the course and to present the findings in a written report. Students will develop skills in the use of Microsoft Excel to support their analysis of the model.
Written Exam 70%, Coursework 30%, Practical Exam 0%
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