MSc Social Research Methods and Statistics

Year of entry: 2024

Course unit details:
Dissertation

Course unit fact file
Unit code SOST65000
Credit rating 60
Unit level FHEQ level 7 – master's degree or fourth year of an integrated master's degree
Teaching period(s) Full year
Available as a free choice unit? No

Overview

In this unit, students will showcase the skills acquired during the taught component of the MSc by planning, conducting and writing up an independent piece of research.

Pre/co-requisites

120 credits in taught component of the program

Aims

In this unit, students will showcase the skills acquired during the taught component of the MSc by planning, conducting and writing up an independent piece of research.

Syllabus

In this unit, students will showcase the skills acquired during the taught component of the MSc by planning, conducting and writing up an independent piece of research.

Teaching and learning methods

The unit does not involve any teaching. Students will have a minimum of 5 one-hour meetings, with project supervisor and 595 independent study hours.

Knowledge and understanding

  • Articulate a specific, policy relevant research question in social science.
  • Accurately apply specific quantitiative/statistical research methods.

Intellectual skills

  • Evaluate the theoretical context of a social statistics research question.
  • Discriminate among various data sources to answer a specific, policy relevant research question.
  • Identify adequate quantitiative methods to answer a specific, policy relevant research question.

Practical skills

  • Undertake a thorough statistical/quantitative analysis and write a convincing research report.
  • Adequately present statistical results via tables, figures, and visualisations and accurately interpret the results of those analysis.
  • Write statistical code in a efficient way, producing readable and well documented code.

Transferable skills and personal qualities

  • Present research ideas suited to social research methods and statistics to a group.

Employability skills

Analytical skills
The dissertation aims to develop and strengthen skills such as problem identification, statistical sound analysis and interpretation of data, which are essential skills in the labour market for many industries. Especially skills in data management and data analytics are well sought after by future employers and will prepare the students for a variety of careers.
Other
Students will be writing statistical code to undertake preliminary descriptive analyses, followed by increasingly sophisticated statistical modelling. They will be using a variety of software, particularly R and Stata, which are both essential skills in the data science and academic job markets. In addition to this, students will be practicing presentation skills through the production of digital visualisations using specialised software.

Assessment methods

Formative Assessment

  • Dissertation plan to be completed for SOST70521 (500 words)

Summative Assessment 

  • Dissertation plan presentation (750 words) 5%
  • Dissertation (9000 words, split as 60% text, 35% code, tables and figures) 95%

Feedback methods

Written feedback on the dissertation plan (completed for SOST70521) provided through Blackboard. 

Verbal feedback during presentation at student conference, or written feedback via Blackboard, or face-to-face meeting with supervisor.

Study hours

Scheduled activity hours
Project supervision 5
Independent study hours
Independent study 595

Teaching staff

Staff member Role
Tina Hannemann Unit coordinator

Return to course details