Teaching & Courses

OQC's main responsability is to develop and deliver high quality quantitative methods courses for Oxford social science undergraduates. 

These courses are now integrated into the curriculae for Philosophy, Politics and Economics (PPE) and History and Politics (HP). Students who are not studying for these degrees, but are interested in quantitative social science, may still take the course and can arrange to do so by contacting the DPIR undergraduate office.

Introductory Quantitative Methods Component in Politics Prelims (Political Analysis)  

Since 2014, the first year Politics Prelims curriculum for students in Philosophy, Politics and Economics (PPE) and History and Politics (HP) includes a third compulsory component, Political Analysis (c), in addition to The Theory of Politics (a) and The Practice of Politics (b). It consists of 8 lectures and 4 data-labs providing an introduction to empirical and quantitative methods.

The purpose of this component is to enable students to assess and critically evaluate better assertions, theories, arguments and opinions expressed in the substantive papers of their degree [component b of the paper]. Throughout their first year, students encounter statements accompanied by quantitative analyses aimed to provide a backing of theoretical statements with empirical evidence. Our knowledge and understanding of politics are largely contingent upon the confirmation or refutation of these statements by the empirical evidence. Statistical tools are essential for researchers to test their claims against the empirical evidence. Basic concepts of statistics, especially randomness and averaging, provide the foundations for measuring concepts, designing studies, estimating quantities of interest and testing theories and conjectures.

This methods component is a gentle introduction to the scientific methods. It consists of an 8-lecture route through the research cycle. Using a running example in the literature, we go through all the steps, from finding a research question up to preliminary statistical analysis. The objective is to learn how statistical methods can help us to address questions of theoretical and/or policy interest. By the end of the course, students will be in position to:

  1. critically read and evaluate statements about causal relationships based on some analysis of data;
  2. summarize quantitative information using software like R and assess the level of uncertainty accompanying these summary estimates.          

One can only learn statistics by doing statistics, so the course includes a four-week, hands-on, laboratory component, where students are introduced to the statistical software R.


The political analysis component is not be assessed in the Prelims examination paper. Instead, students are required to submit one methods essay during Trinity Term.

Quantitative Methods Component in Core Papers Comparative Politics (201), International Relations (214) & Political Sociology (220)

The​ ​study​ ​of​ ​politics​ ​requires​ ​assessing​ ​claims​ ​about​ ​the​ ​relationships​ ​among​ ​political​ ​actors, political​ ​institutions, ​ ​and​ ​societal​​outcomes. ​This​ ​course​ ​will​ ​help​ ​students​ ​critically​ ​assess claims​ ​made​ ​in​ ​academic​ ​literature​ ​and​ ​build​ ​the​ ​skills​ ​necessary​ ​to​​analyse​ ​these​ ​relationships themselves.

The​ ​course​ ​is​ ​designed​ ​as​ ​a​ ​complement​ ​to​ ​three​ ​core​ ​papers​ ​in​ ​Politics:​ ​Comparative Government​ ​(201),​ ​International​​Relations​ ​(214),​ ​and​ ​Political​ ​Sociology​ ​(220).​ ​Each​ ​of​ ​these papers​ ​asks​ ​students​ ​to​ ​critically​ ​evaluate​ ​empirical​ ​evidence;​ ​for​​example,​ ​recent​ ​exams​ ​have asked​ ​students​ ​to​ ​assess​ ​the​ ​effects​ ​of​ ​federalism​ ​(CG),​ ​the​ ​mass​ ​media​ ​(PS),​ ​and​ ​globalization (IR).​ ​Our​ ​main​ ​goal​ ​is​ ​to​ ​give​ ​students​ ​the​ ​tools​ ​to​ ​engage​ ​critically​ ​with​ ​the​ ​evidence​ ​they encounter​ ​in​ ​their​ ​core​ ​papers​ ​in​​ Politics,​ ​which​ ​will​ ​help​ ​them​ ​make​ ​better​ ​assessments​ ​of quantitative​ ​evidence​ ​both​ ​in​ ​exam​ ​questions​ ​like​ ​these​ ​and​ ​in​ ​a​​much​ ​broader​ ​set​ ​of circumstances​ ​after​ ​their​ ​degree​ ​is​ ​completed.


Students​ ​may​ ​choose​ ​between​ ​two​ ​forms​ ​of​ ​assessment. ​In​ ​either​ ​case, ​ ​the​ ​assignment​ ​should​ ​be submitted​ ​via​ ​Weblearn​ ​by​​noon​ ​on​ ​Friday​ ​of​ ​Week​ ​2​ ​of​ ​Hilary​ ​Term.

Option​ ​1: ​ ​Take-home​ ​exam

The​ ​take-home​ ​exam​ ​consists​ ​of​ ​specific​ ​questions​ ​about​ ​the​ ​content​ ​taught​ ​in​ ​the​ ​lab​ ​sessions. For​ ​example, ​ ​students​ ​may​ ​be​​given​ ​a​ ​dataset​ ​and​ ​asked​ ​to​ ​run​ ​some​ ​analysis​ ​and​ ​interpret​ ​the results. ​ ​The​ ​take-home​ ​exam​ ​will​ ​be​ ​distributed​ ​in​ ​Week​ ​8​ ​of​​Michaelmas​ ​Term.

Option​ ​2: ​ ​Essay​ ​based​ ​on​ ​data​ ​analysis

Students​ ​pursuing​ ​this​ ​option​ ​will​ ​write​ ​an​ ​essay​ ​of​ ​no​ ​more​ ​than​ ​2,000​ ​words​ ​in​ ​which​ ​they report​ ​the​ ​results​ ​of​ ​original​ ​data​​analysis.​ ​This​ ​option​ ​is​ ​designed​ ​to​ ​allow​ ​students​ ​the​ ​freedom to​ ​pursue​ ​a​ ​topic​ ​or​ ​question​ ​that​ ​they​ ​find​ ​interesting,​ ​with​ ​the​​possibility​ ​that​ ​their​ ​analysis could​ ​be​ ​the​ ​first​ ​stage​ ​of​ ​a​ ​dissertation​ ​project.​ ​In​ ​general​ ​these​ ​essays​ ​should​ ​go​ ​well​ ​beyond what​ ​we​ ​do​ ​in​ ​the​ ​lab​ ​worksheets​ ​by​ ​using​ ​different​ ​data​ ​or​ ​additional​ ​methods​ ​or​ ​both.​ ​In previous​ ​years,​ ​a​ ​small​ ​minority​ ​of​​students​ ​chose​ ​this​ ​option.

Quantitative Methods Dissertation (298)

Third year students have the option of writing a supervised dissertation, applying quantitative methods to an area of Politics, International Relations or Sociology.  This counts as one of their eight subjects for Finals.  

The dissertation must be 15,000 words, and is supervised through individual tutorials, as well as Data Lab sessions.