We use cookies to ensure that we give you the best experience on our website. You can change your cookie settings at any time. Otherwise, we'll assume you're OK to continue.

# Archive Module Description

No such Code for pgprog: N1KD17
No such Code for pgprog: N1KB17

## Department: Management and Marketing

### BUSI41I15: MODELLING AND ANALYSIS FOR MANAGEMENT (EXECUTIVE)

Type Level Credits Availability Tied 4 15 Not available in 2021/22
Tied to N1KD17 N1KB17

• None.

• None.

• None.

#### Aims

• To provide students with a sufficiently detailed knowledge of methods for solving quantitative problems to permit them to appreciate material covered elsewhere in the MBA programme.

#### Content

• Data description.
• The Normal distribution.
• Inference: means, proportions, contingency tables (Chi-squared).
• Applications of statistical models to management problems, e.g. risk and monitoring.
• Linear models: simple regression and applications; introduction to linear programming.

#### Learning Outcomes

Subject-specific Knowledge:
• By the end of this module, students should have a detailed knowledge of key concepts in data description and statistical modelling; monitoring and hypothesis testing; and linear models.
Subject-specific Skills:
• By the end of this module, students should:
• Be able to use a range of standard statistical tests and apply them to complex management problems;
• Be able to use modelling applications within Excel and apply them to complex management problems.
Key Skills:
• Written communication.
• Planning, organising and time management.
• Problem solving and analysis.
• Using initiative.
• Computer literacy.

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

• Learning outcomes will be met through a combination of lectures, groupwork, case studies, practical (computer) classes and discussion, supported by guided reading. The summative assessment, by written assignment, will test students' understanding of and ability to apply relevant analytical techniques.

#### Teaching Methods and Learning Hours

Activity Number Frequency Workshops (a combination of lectures, groupwork, case studies, practical (computer) classes and discussion) 28 ■ Preparation and Reading 122 Total 150

#### Summative Assessment

Component: Written Assignment Component Weighting: 100%
Element Length / duration Element Weighting Resit Opportunity
Written Assignment 4,000 words maximum 100%

#### Formative Assessment:

Quantitative exercises.

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