MA Politics

Year of entry: 2024

Course unit details:
Tools and techniques of applied quantitative analysis

Course unit fact file
Unit code POLI60341
Credit rating 15
Unit level FHEQ level 7 – master's degree or fourth year of an integrated master's degree
Teaching period(s) Semester 1
Available as a free choice unit? Yes


POLI60341 is designed to deliver a rigorous grounding in quantitative methods sufficient for independent use of such methods in MA dissertations or PhD research. It aims to offer a balanced mix of training, helping to prepare advanced students who want to engage in secondary data analysis in their MA dissertation or in doctoral research and have some experience of quantitative methods, but also aiming to provide a robust initial grounding who have not received extensive quantitative methods training prior to joining the MA..


POLI60341 is relevant for students with diverse academic backgrounds and interests who are interested in developing and applying quantitative methods.  It will teach students how to find relevant data for a range of research questions, and explore the limitations and common pitfalls of analysing quantitative data. For all those looking to understand and use data in politics masters and doctoral research, POLI60341 provides an essential step forward in the basic core skills of data evaluation and analysis, as well as introducing more complex statistical techniques that are not typically taught at undergraduate level. It is particularly designed to enable students to conduct work more independently, from finding their own data sources, analysing them and writing up the results for an independent research project. It will be taught using STATA - an advanced statistical software package that is more sophisticated and flexible than SPSS, the package typically used in UG quantitative methods courses

Teaching and learning methods

10 x 2 hour computer lab sessions


Knowledge and understanding

  • Learn how to find, use and analyse quantitative data using the most popular quantitative data analysis techniques to answer questions driving political research, and how to write up the findings from such analysis
  • Learn about how academics researching politics gather and use data, with guest lectures from various quantitative researchers in the department explaining how they apply particular techniques to solve particular research problems
  • Learn about which questions can be answered with quantitative data and which cannot.


Intellectual skills

  • Evaluate data from the point of view of quality, design and method of collection;
  • Develop a critical awareness of the strengths and weaknesses of different methods of analysing data and applying the results of quantitative analysis to political research questions;
  • Understand and analyse some of the central questions in politics research that have been addressed with the use of quantitative data;

Practical skills

  • Develop a critical awareness of the use of data in political and media debate;
  • Gain an ability to seek out relevant data sources

Transferable skills and personal qualities

  • Improve the ability to interpret and communicate quantitative findings in writing and verbally.
  • Gain an exposure to widely used quantitative political science data sources
  • Gain an ability to conduct a range of basic to intermediate data analysis techniques, including cross-tabulation analysis, graphical analysis and basic regression analysis
  • Gain a working knowledge of STATA, the most widely used statistical software for applied quantitative analysis

Assessment methods

Method Weight
Other 45%
Report 55%


Length required


Four learning logs of c.450 words each: these will test your understanding of the statistical and analytical techniques we have learned, how to apply them, and how to interpret and write up results



End of course report: This report is a more extended piece of writing, where you will need to develop and motivate a hypothesis, explain the data and measures you will use to test it, then present and interpret an extended data analysis examining it. This should feature examples of data visualization (graphs), basic analysis (tables and cross-tabulation) and at least one form of statistical modelling (regression analysis).



Weekly workshop output: you will need to record your activities in each week’s workshop in a stata “do file”. These will be checked to ensure engagement with and understanding of the workshop activities, and formative feedback provided to help you with the learning logs and course report




Study hours

Scheduled activity hours
Practical classes & workshops 20
Independent study hours
Independent study 130

Teaching staff

Staff member Role
Robert Ford Unit coordinator

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