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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2020/2021

Information in the Degree Programme Tables may still be subject to change in response to Covid-19

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DRPS : Course Catalogue : Business School : Common Courses (Management School)

Postgraduate Course: Quantitative Research Methods (CMSE11436)

Course Outline
SchoolBusiness School CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits15 ECTS Credits7.5
SummaryQuantitative Research Methods aims to introduce students to research idea generation, ethics, and basic quantitative methods in business area for their dissertation. It helps students choosing dissertation topic, questions and facilitates all necessary quantitative methods that are required for that major piece of independent research as well as their future work in business area.
Course description Academic Description

The course provides students with an understanding of the research process and a thorough introduction to quantitative (as well as basics of qualitative) research method. The course equips students with the skills and knowledge necessary to prepare for a significant research project using quantitative research methods.

Outline Content

What is Research?
Basics of Quantitative Research
Basic of Qualitative Research
Research Ethics and Integrity
Data Collection, organisation and representation
Data sampling, confident interval
Hypothesis testing
Analysing two variables, simple linear regression
Analysing multiple variables multi-variate regression (with SPSS lab)
Advanced method, logistic regression and decision tree (with SPSS lab)

Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2020/21, Not available to visiting students (SS1) Quota:  None
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 150 ( Lecture Hours 20, Seminar/Tutorial Hours 8, Programme Level Learning and Teaching Hours 3, Directed Learning and Independent Learning Hours 119 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) Individual Project (100%) (assess all learning outcomes)

Assessment is based on a mini data analysis project with three deliveries: Excel spreadsheet, SPSS project file, or Stata scripts and a 1000-word report (the Office 365, SPSS, Stata can be accessed throught he on-campus lab or remotely installed to personal laptop through the school software link: https://www.ed.ac.uk/information-services/computing/desktop-personal/software/staff-students)

Students will be provided with a dataset with at least 1000 records and 50 attributes and will be asked to:

- Clean the noise and remove the empty items in the dataset

- Model the data using the range of quantitative methods introduced in this course, including linear regression, logistic regression, and decision tree, using both Excel and SPSS appropriately

- Prepare an annotated spreadsheet and documented SPSS project file to explain how the data was modelled

- Critically evaluate, analyze, and explain the results of each method in a brief report
Feedback Generic and individual feedback will be given within 15 days of the submission deadline, in line with the University of Edinburgh Taught Assessment Regulations.
A Q&A session based on the mini-project will also be organised. The 'Think-Pair-Share' strategy will be used to gauge levels of understanding of key concepts.
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Identify the role of quantitative method in the discipline of business.
  2. Understand the differences between quantitative and qualitative research methods.
  3. Plan and conduct different methods of data collection and understand research ethics requirements.
  4. Analyse different forms of quantitative data.
  5. Understand and be able to use different quantitative methods for data analysis.
Reading List
Paolo Brandimarte (2011), Quantitative Methods: An Introduction for Business Management (2011). Wiley
Additional Information
Graduate Attributes and Skills Demonstrate and/or work with:
- Knowledge that covers and integrates most of the main areas of the subject/discipline/sector including their features, boundaries, terminology and conventions.
- A critical understanding of a range of specialised theories, concepts and principles.
- Extensive, detailed and critical knowledge and understanding in one or more specialisms, much of which is at, or informed by, developments at the forefront.
- A critical awareness of current issues in a subject/discipline/sector and one or more specialisms.

Apply knowledge, skills and understanding:
- In applying a range of standard and specialised research and/or equivalent instruments and techniques of enquiry.
- In planning and executing a significant project of research, investigation or development.
- In demonstrating originality and/or creativity, including in practices.


Apply critical analysis, evaluation and synthesis to forefront issues, or issues that are informed by forefront developments in the subject/discipline/sector.
- Identify, conceptualise and define new and abstract problems and issues.
- Develop original and creative responses to problems and issues.
- Critically review, consolidate and extend knowledge, skills, practices and thinking in a subject/discipline/sector.
- Deal with complex issues and make informed judgements in situations in the absence of complete or consistent data/information.

Communication, ICT, and Numeracy Skills
- Use a wide range of routine skills and a range of advanced and specialised skills as appropriate to a subject/discipline/sector, for example:
- Communicate, using appropriate methods, to a range of audiences with different levels of knowledge/expertise.
- Communicate with peers, more senior colleagues and specialists.
- Use a wide range of ICT applications to support and enhance work at this level and adjust features to suit purpose.
- Undertake critical evaluations of a wide range of numerical and graphical data
- Exercise substantial autonomy and initiative in professional and equivalent activities.
- Take responsibility for own work and/or significant responsibility for the work of others.
Special Arrangements Only available to MSc International Business and Emerging Markets and MSc Management students.
KeywordsNot entered
Contacts
Course organiserDr Yi Cao
Tel: (0131 6)51 5338
Email: Yi.Cao@ed.ac.uk
Course secretaryMiss Fionna Ogilvie
Tel: (0131 6)51 3028
Email: Fionna.Ogilvie@ed.ac.uk
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