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Semester 1

Decision Analytics (BUST10133)

Subject

Business Studies

College

CAHSS

Credits

20

Normal Year Taken

3

Delivery Session Year

2023/2024

Pre-requisites

Visiting students must have completed 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.

Course Summary

This course provides students with an understanding of the techniques available for the analysis of management problems in which uncertainty plays a significant role.

Course Description

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. Outline Content 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.

Assessment Information

Written Exam 70%, Coursework 30%, Practical Exam 0%

view the timetable and further details for this course

Disclaimer

All course information obtained from this visiting student course finder should be regarded as provisional. We cannot guarantee that places will be available for any particular course. For more information, please see the visiting student disclaimer:

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