Course Catalogue

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The dissertation is an independent, original research project of up to 10,000 words (±10%) words undertaken within the student's chosen programme track. It enables students to investigate a research question of academic relevance and communicate their findings in a scholarly dissertation.

To build up their research skills for the dissertation, students follow the course "Research Methods and Dissertation Training".

Prior to commencing the project, students complete the Research Methods and Dissertation Training course, comprising 20 hours of lectures and laboratory classes in Semester 1 and 16 hours in Semester 2. In addition, students attend one 2-hour Stata laboratory session in Semester 2.

For students on the MSc in Data Analytics for Economics and Finance programme, where equivalent research methods and analytical training are already embedded within the curriculum, this course serves as a supplementary learning resource. For students on the other programmes listed in Table 10, it provides structured preparation for undertaking the dissertation.

Dissertation supervision is provided from May to August. During this period, students receive 4 hours of academic supervision from an allocated supervisor.

Students need to meet the requirements for progression to the dissertation based on the taught courses of the programmes as detailed in the Code of Assessment.

Industry Project

None

A dissertation of 10,000 (±10%) words completed under the guidance of the academic supervisor.

This course aims to:

■ Enable students to undertake independent postgraduate research by critically evaluating and synthesising academic literature to formulate and justify a research question.

■ Develop students' ability to design and implement an appropriate research strategy by selecting and applying suitable research methods, statistical, econometric and other analytical techniques, including relevant digital tools, to investigate a research question.

■ Develop students' ability to apply appropriate statistical, econometric and other analytical techniques, including the use of relevant digital tools, to collect, manage, analyse and present empirical evidence in support of a research question.

■ Develop students' capacity to critically evaluate empirical models, analytical approaches and research findings, recognising their assumptions, limitations and contribution to existing knowledge.

■ Develop students' ability to communicate research effectively through a rigorous, well-structured dissertation that demonstrates intellectual independence, scholarly integrity and academic rigour.

By the end of this course students will be able to:

1. Critically evaluate and synthesise relevant academic literature to formulate, justify and refine a clear, original research question.

2. Design and justify an appropriate research strategy by selecting suitable research methods and analytical techniques to address the research question or hypothesis.

3. Apply appropriate research methods, analytical techniques and relevant digital tools to collect, manage, analyse and interpret qualitative and/or quantitative evidence, including statistical and econometric methods where appropriate.

4. Critically evaluate empirical models, analytical approaches and research findings to draw well-supported conclusions, recognising their assumptions, limitations and contribution to existing knowledge.

Produce a rigorous and well-structured scholarly dissertation that demonstrates intellectual independence, effective academic writing, scholarly integrity and accurate referencing.