Postgraduate Course: Quantitative Methods and Tools (MBA) (CMSE11243)
||College||College of Humanities and Social Science
|Credit level (Normal year taken)||SCQF Level 11 (Postgraduate)
||Availability||Not available to visiting students
|Summary||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 incorporates 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.
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
Statistical reporting and presentation.
Student Learning Experience
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.
Entry Requirements (not applicable to Visiting Students)
||Other requirements|| For Business School PG students only, or by special permission of the School. Please contact the course secretary.
Course Delivery Information
|Academic year 2018/19, Not available to visiting students (SS1)
|Learning and Teaching activities (Further Info)
||Please contact the School directly for a breakdown of Learning and Teaching Activities
|Additional Information (Learning and Teaching)
This zero credit course is designed to help students prepare for other courses in the programme.
|Assessment (Further Info)
|Additional Information (Assessment)
||In-Class Test 100%
The course incorporates 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.
||Students will receive feedback throughout the duration of the course: after the initial diagnostic test, after the mid-term progress test and after the summative end-of-course test. In addition continuous feedback is provided during the small-group tutorials.
Feedback on formative assessed work will be provided within 15 working days of submission, or in time to be of use in subsequent assessments within the course, whichever is sooner. Summative marks will be returned on a published timetable, which has been made clear to students at the start of the academic year.
Students will be provided with electronic written feedback for all coursework.
|No Exam Information
On completion of this course, the student will be able to:
- Recognise and critically discuss quantitative techniques suitable for data analysis in particular management situations.
- Critically discuss the underlying assumptions, uses and limitations of these techniques.
- Apply statistical and basic spreadsheet modelling techniques and to correctly interpret the results
- Use Microsoft® Excel® for basic modelling and data analysis.
|Reading material will be provided at the start of the course.|
|Graduate Attributes and Skills
||Subject Specific Skills
Recognise quantitative techniques suitable for data analysis in particular management situations.
Apply statistical and basic spreadsheet modelling techniques and to correctly interpret the results.
Use Microsoft® Excel® for basic modelling and data analysis.
Collect, summarise, analyse and present data.
Construct, interpret and communicate statistical information correctly, coherently and precisely.
|Additional Class Delivery Information
||This zero credit course is designed to help students prepare for other courses in the programme. It consists of 2-6 hours of computer-based tests, up to 80 hours of self-study (including video lectures and tutorials), up to 4 hours of preparatory reading for tests and 10 hours of small-group teaching (revision classes in computer lab).
|Keywords||Data Analysis Quantitative Research Statistics
|Course organiser||Dr Peter Flett
Tel: (0131 6)51 1039
|Course secretary||Mrs Angela Muir
Tel: (0131 6)51 3854