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Quantitative Dissertation

Module description

A good dissertation is a core element of a successful Masters degree. It equips you with key, transferable research skills that will be invaluable to your career whether you decide to take up PhD research or not. A dissertation is not a long essay. It has a certain number of core components that must be evident to varying degrees. Like a good essay, it must demonstrate research skills, independent learning, good organization of complex material, clarity and erudite expression. But a Masters dissertation will be driven primarily by your own original research, research questions you devise and the data you want to analyse. It will be a mark of your initiative, independence and inquisitiveness. You should expect to start thinking about and working on your dissertation immediately on beginning the Programme. Given that that AQM is an eminently quantitative programme aimed at training you in state-of-the-art statistical, econometric and related techniques, your dissertation – while driven by your substantive interests – will have to make use of some of the tools and methods you learned during the programme. 

Module aims - intentions of the module

To enable you to write an extended piece of independent writing, around a topic of your own choosing using some of the quantitative data-analytic tools you became acquainted with during the programme (e.g., methods for causal inference, Bayesian econometrics, network analysis, text-mining and analysis techniques), in communication with key experts in your chosen area. It will allow you to demonstrate depth and breadth of knowledge in a particular subject area of professional or intellectual interest. The dissertation will be a mark of your ability to express yourself in writing.

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

• 1. Demonstrate knowledge in depth of a specialised subject area (may include a specific statistical technique)
• 2. Design an individual research programme, incorporating appropriate quantitative social science research methods
• 3. Collate and analyse primary or secondary data related to a subject discipline from appropriate sources.

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

• 4. Assimilate and critically analyse data from an appropriate range of sources, from primary or secondary data sets
• 5. Develop cogent argument and apply appropriate statistical techniques
• 6. Communicate complex information and ideas effectively in writing.

ILO: Personal and key skills

On successfully completing the module you will be able to...

• 7. Use IT for information retrieval and presentation.
• 8. Manage own work

Syllabus plan

At least four supervision meetings per term.  There is an initial meeting to plan the dissertation followed by three meetings to give academic guidance including specific feedback on draft work. 

Learning activities and teaching methods (given in hours of study time)

Details of learning activities and teaching methods

Formative assessment

Summative assessment (% of credit)

Details of summative assessment

Details of re-assessment (where required by referral or deferral)

Indicative learning resources - Basic reading

G King, R Keohane and S Verba, Designing Social Inquiry (Princeton UP, 1994);

D Burton (ed), Research Training for Social Scientists: A Handbook for Postgraduate Researchers (Sage, 2000).

S. Jackman. Bayesian Analysis for the Social Sciences (Wiley, 2000).

W. Greene. Econometric Analysis (Pearson, 2012).

Angrist, J., and Pishke, S. Mostly Harmless Econometrics (Princeton University Press, 2009).

Gelman, Andrew, and Jennifer Hill. Data analysis using regression and multilevel/hierarchical models. Cambridge University Press, 2006.

Kosuke, I.. Quantitative Social Science: An Introduction. (Princeton University Press, 2017)

Wooldridge, J. Econometric Analysis of Cross-Section and Panel Data (2010, MIT University Press).

Subject-specific reading will varying according to research topic.

Key words search

Advanced Quantitative Methods Dissertation, AQM MRes