Module BUSI48O15: MODELS FOR DECISION (FT)

Department: Management and Marketing

BUSI48O15: MODELS FOR DECISION (FT)

Prerequisites

• None

Corequisites

• None

Excluded Combination of Modules

• None

Aims

• To provide a knowledge of and ability with a range of quantitative models used in aiding management decisions.
• To provide an appreciation of the purpose and role of statistical method in management.
• To make familiar quantitative approaches to management decision models in conditions of risk and uncertainty.
• To show how optimisation approaches can help in management decision and, in particular, provide an ability to use the linear programming model.

Content

• Data description, quantitative and graphical.
• Probability and probability models (e.g. Normal).
• Inference about means, proportions and contingency tables.
• Simple regression and correlation with application (e.g. time series).
• Models for decision characterised by uncertainty and risk.
• Optimisation using linear programming.

Learning Outcomes

• By the end of the module students should have sufficient knowledge of a range of quantitative models to be able to apply them critically to management problems.

• By the end of the module students should be able to:
• identify models appropriate for aiding solutions to some key management problems;
• apply relevant statistical methods;
• be aware of the difference between uncertainty and risk and apply appropriate methods;
• apply linear programming optimisation.

• Problem identification
• Preparation of written reports
• Presentation of results to groups
• Planning and organising
• Use of software

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• The module is delivered in blocks, timetabled internally, hence the number/frequency/duration of individual blocks may vary but the overall total contact time will be 32 hours.
• Blocks typically involve a mix of lecture input, groupwork, computer classes, presentations and discussion, supported by guided reading.
• The summative assignment will test ability to formulate a problem and apply appropriate methods. The formative assessment will be various tasks set at the end of each session. The object is to provide students with feedback on the development of their technical skills and their understanding of application. Although this is given for each session a larger task is given about halfway through the module which requires an extended application of statistical methods before moving to operational research topics. This larger exercise is discussed in more detail and is signalled as the main formative task. Submissions are marked and solutions discussed in class.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

After each session a number of tasks are set, for instance some numerical exercises or critical commentary on a paper. Of these tasks one or two will be identified as the basis for discussion at the start of the following session. The remainder are for the interest of students and for those who need a little more practice with technique. Solutions are put on DUO following discussion.

■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University