Postgraduate Course: Quantitative Methods and Tools (MBA) (CMSE11243)
Course Outline
| School | Business School |
College | College of Humanities and Social Science |
| Course type | Standard |
Availability | Not available to visiting students |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Credits | 0 |
| Home subject area | Common Courses (Management School) |
Other subject area | None |
| Course website |
None |
Taught in Gaelic? | No |
| Course description | This non-credit bearing course aims to develop an understanding of basic probability, statistics and spreadsheet modelling techniques to support management decision-making. The course is designed to help underpin the quantitative approaches used in the core MBA courses but also to provide a basis for the later use of quantitative techniques in the elective options, consultancy and capstone projects. The course will incorporate an initial diagnostic test to assess participants¿ entry skills, a mid-term test to assess progress and a summative test to assess levels of achievement. |
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | For Business School PG students only, or by special permission of the School. Please contact the course secretary. |
| Additional Costs | None |
Course Delivery Information
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| Delivery period: 2014/15 Semester 1, Not available to visiting students (SS1)
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Learn enabled: Yes |
Quota: None |
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Web Timetable |
Web Timetable |
| Course Start Date |
15/09/2014 |
| Breakdown of Learning and Teaching activities (Further Info) |
Please contact the School directly for a breakdown of Learning and Teaching Activities |
| Additional Notes |
|
| Breakdown of Assessment Methods (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
| No Exam Information |
Summary of Intended Learning Outcomes
Knowledge and Understanding:
¿ A range of basic quantitative techniques that can be used to summarise and analyse data to support decision-making.
¿ The underlying assumptions, uses and limitations of these techniques.
¿ The practical use of statistical and basic spreadsheet modelling techniques in management decision-making.
Subject Specific Skills:
¿ The ability to recognise quantitative techniques suitable for data analysis in particular management situations.
¿ The ability to apply statistical and basic spreadsheet modelling techniques and to correctly interpret the results.
¿ The ability to use Microsoft® Excel® for basic modelling and data analysis.
Transferable skills
¿ Ability to collect, summarise, analyse and present data.
¿ Ability to construct, interpret and communicate statistical information correctly, coherently and precisely.
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Assessment Information
In-Class Tests 100%
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Special Arrangements
| None |
Additional Information
| Academic description |
Not entered |
| Syllabus |
Data exploration and summary: sources and types of data, descriptive statistics and methods of displaying data (methods to describe the distribution of a single variable, methods to find relationships among variables); probability: basic concepts in probability, major discrete and continuous probability distributions; Statistical inference: sampling methods and distributions, confidence interval estimation, hypothesis testing. Spreadsheet modelling with Microsoft® Excel®: workbooks, worksheets, cells, functions, toolbars, data import/export, best practice for good spreadsheet layouts, pivot tables, Analysis ToolPak; statistical reporting and presentation.
The teaching and learning approach will include independent reading, self-study, online lectures/tutorials and a series of lectures and workshops to reinforce key techniques. |
| Transferable skills |
Not entered |
| Reading list |
Not entered |
| Study Abroad |
Not entered |
| Study Pattern |
Not entered |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Maurizio Tomasella
Tel:
Email: Maurizio.Tomasella@ed.ac.uk |
Course secretary | Miss Kate Ainsworth
Tel: (0131 6)51 3854
Email: Kate.Ainsworth@ed.ac.uk |
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