Oxford Q-Step Centre


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Keep in touch with the latest news, blog posts and other information from the Oxford Q-Step Centre.

Oxford Q-Step Centre

Random Walk: OQC Blog

Random Walk, is the Oxford Q-Step Centre Blog, with entries written by a range of professionals on a range of subjects within quantitative methods.

Keep checking back for updated entries, and don't forget to let us know what you think in the comments section!

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Politics in Spires Blog

Politics in Spires is a collaboration between the members of the Department of Politics and International Relations at the University of Oxford, and the Department of Politics and International Studies (POLIS) at the University of Cambridge. Our aim is to bring academic analysis to broader discussions about politics.

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Oxford Q-Step Centre funds a number of undergraduate internships over the summer, each of which requires specific data-handling.  Here is some of the feedback: 


Internships: Host Organisations


Internship sponsor form

Jobs & Internships

Information on job and internship possibilities is coming soon!



                               ‘Is data good for democracy?’


Thank you to all of the entrants for Oxford Q-Step Centre's inaugural Schools' Essay Competition.  


We had a terrific response, and the judges were extremely impressed with the quality of the work - the structure, research and analysis.

Winner of the First Prize is Sophie Cogan from Skipton Girls' High School in West Yorkshire.

Second Prize was awarded to Fareeha Masood from Kendrick School in Berkshire.


You can read both essays here:

First Prize - Sophie Cogan - Is Data Good for Democracy?

Second Prize - Fareeha Masood - Is Data Good for Democracy?


To find out more about Oxford Q-Step Centre, follow us on Twitter @OxfordQstep or on Facebook @oxfordqstepcentre.




Call for applications:

Oxford QStep Centre Undergraduate Research Support Grants


The Oxford QStep Centre invites Oxford undergraduates to apply for a grant to support social science research involving quantitative methods.

Research support grants are designed to allow recipients to run surveys, digitize source data, or undertake other tasks necessary to complete a dissertation or other research project. Students could design a questionnaire to be fielded by a survey company like YouGov or via a crowdsourcing platform like Mechanical Turk; they could specify a data collection task to be undertaken by a data collection company like Digital Divide Data or through a platform like Upwork; they could purchase data for use in their research; or they could purchase software or hardware that allows them to undertake specific research tasks.

Although we imagine most students will use grants to support dissertation research, we also encourage students to consider applying for grants to undertake other types of research. For example, a student may wish to undertake an independent research project about an industry or organization, possibly with guidance or cooperation from a non-academic supervisor. In these cases, the grants provide an opportunity for a student to obtain funding for a self-designed internship. To the extent possible, such a project should have a well-defined output.

We are particularly interested in supporting students who would not be able to conduct the specified research without grant support. We expect most grants to be under £500 each, but we would consider a larger grant in a compelling case. Grants will be awarded on a rolling basis (i.e. with no fixed deadline), but funds are limited so applying earlier will give the best chance of success. Any further questions about the modalities and process of the application can be submitted here or sent directly to This email address is being protected from spambots. You need JavaScript enabled to view it.

Application instructions

Applications should be sent to This email address is being protected from spambots. You need JavaScript enabled to view it.. A complete application includes:

  • Contact information for the applicant
  • Contact information for the student’s supervisor on the research project or, if supervisor has not been determined, college tutor
  • A brief description of the research project (up to 500 words), including details on the use of quantitative methods
  • A budget and accompanying explanation (up to 250 words) justifying the funding requested

Criteria for success

  • Quality of proposed project, including prospect for success and nature of output
  • Clarity of what funds will be used for
  • Feasibility of project (including given circumstances surrounding COVID-19)
  • Support from the supervisor or college tutor
  • If the research is not for a dissertation, clear indication of what research output will be

After completion of the project, grant recipients will be asked to provide a report on their use of funds; they may also be invited to describe their project in an event including all grant recipients.





Here you can find useful links and videos on statistical terms and concepts. As you will see, people have thought of various creative ways to introduce and explain statistics. Watching these videos might help you clarify key terms and concepts more than many textbooks do.


Useful videos to introduce and explain statistics in a more visual and creative way.

See our wall of student faces and connect with our students' thoughts and experiences with the Oxford Q-Step Centre.


Resources explaining statistical terms and concepts for our Q-Step courses.


In this seminar we review the basic principles of text analysis in the context opinion mining of social media data, i.e. the case where the signal to noise ratio is usually low. After a brief excursus on different techniques of text analysis we present in details one specific approach called "ReadMe", due to Hopkins and King (2010). This technique has proven to be highly efficient in the context of social media analysis. Contrary to all other methods, the ReadMe approach focuses on the estimation of the aggregated distribution of the opinions rather than individual classification of texts. This allows for great accuracy in the final estimation at the cost of loosing individual classification properties, but this is not a real issues in social science research as we will show through several examples.

Some improvements over the original ReadMe algorithm will also be presented.


Daniel Hopkins and Gary King, 'A Method of Automated Nonparametric Content Analysis for Social Science', American Journal of Political Science, 54, 1 (January 2010): 229--247.

Please see here for tickets and further information: http://www.politics.ox.ac.uk/departmental/twitter-big-data-and-and-social-science.html


Statistics icon


Explore the fun world of statistics!

Statistics: What is it all about?

We deal with statistics almost in every part of our lives. What is the likelihood that it will rain tomorrow or that the sun will shine? What is the average mark of an Oxford Politics student in finals? We live in a probabilistic world in which certainty is rare. Therefore, when we study Politics, gaining an in-depth understanding of statistics is crucial. What are the changes that democracy will stabilize in a country that recently survived a coup? Are people more likely to turnout in an election when they have been reminded of their civic duty to vote in a campaign ad? Or is it indeed the case that democracies are less likely to go to war with each other? In order to answer these questions and to engage critically with then an understanding of Quantitative Methods is key.

Statistics: Why should I know about them?

  • Statistics provide ideas and tools for probing data to advance our understanding of the world. Statistical ideas highlight how best to collect, analyse, and present data. Statistical tools allow us to learn about a population by looking at just a sample of it, to summarise large amounts of data to be able to make sense of them, and to study variation to understand what actually makes the difference. Statistics are exciting tools that help us to channel our creativity to understand politics, society, and modern life.
  • Statistics prepare you well for future careers. As data become increasingly available, the need for graduates who are able to make sense of them increases too. Statistics equip students with the tools to make sense of data, and increase their chances on the job market. The private sector, civil service, non-governmental organisations, the media, polling institutes, and many others demand graduates with statistical knowledge. As The New York Times put it recently: ‘For Today’s Graduate, Just One Word: Statistics’.

Statistics: How best can I learn about them?

OQC will help its graduates develop the statistical tools you need to become more marketable on the job market. It provides students opportunities to acquire practical experience with statistics in the work place through a programme of work placements. Students are able to apply for bursaries through the OQC work placement programme. The OQC tutors can advise students about the possibility of graduate study in the Social Sciences with a Quantitative Methods focus.

Further information: Course and Resources.

Statistics: How best can I teach them?

We will be building a resource section for teachers shortly.

Statistics: Internships & Jobs

Details on this will be added shortly.


Summer Institute 2016

Students at the inaugural Summer Institute give their views ....

Teachers’ Workshop – Effective Use of Data in EPQs

ESRC Programme

Oxford Q-Step Centre ran a one-day workshop for teachers who supervise Extended Project Qualifications in Social Sciences, to help them support and advise their students on the effective use of data in their dissertations.   The course was part of the Economic & Social Research Council’s Festival of Social Science 4-11 November 2017.

The Programme:

The aim was to give teachers, and through them their students, confidence to use data effectively and appropriately. The course introduced different ways of gathering, analysing and presenting statistics and how to use GoogleSheets and RStudio.

Here are the supporting powerpoints and information sheets.

How could data be used in an EPQ?

Data Resources

A Brief, Non-technical Introduction to Regression

Finding and Merging Data


Text as Data - How do social scientists control what we measure using quantitative text analysis methods?  How far, and how successfully, can we quantify it?  Professor Ben Lauderdale, from the LSE, is giving a Masterclass on the latest developments in this fast-moving field at 2 pm on Tuesday 24 May, in the Lecture Theatre of the Department of Politics & International Relations, Manor Road Building.

Register for free at http://www.politics.ox.ac.uk/departmental/dpir-text-analysis-masterclass-how-do-we-control-what-we-measure-using-quantitative-text-analysis-methods.html