Advanced Quantitative Methods

Page contents

• Programme overview
• Entry requirements
• Staff research interests

Programme overview

The Advanced Quantitative Methods (AQM) pathway is for social scientists who wish to learn advanced quantitative methods for secondary-data analysis, and apply these methods appropriately to answer particular substantive questions from their disciplines. This includes social scientists interested in inter-disciplinary research involving the application of quantitative methods from one discipline to problems in another.

The AQM pathway is also for statistically trained researchers whose interests are more methodological. Projects may involve applying statistical methods used in other disciplines to social science problems, or developing novel statistical methods for analysing social-science data. We welcome applications from students with backgrounds in statistics or related disciplines.

Research groups

The ESRC has designated AQM as a priority area, and the purpose of the pathway is to provide training and supervision that emphasizes quantitative methods to a higher level than is usually offered. Training includes a structured programme of core AQM courses and a fortnightly research and reading group.

Details of the core training currently offered can be found on the AQM courses website.

Key research interests

You will need two supervisors: one supervisor with AQM expertise and one supervisor with expertise in your chosen substantive area. Your main supervisor must be from a social science discipline.

The following AQM course leaders are all potential supervisors with AQM expertise:

• Dr Paul Clarke
• Dr Rich Harris
• Professor Kelvyn Jones
• Dr George Leckie
• Dr David Manley
• Professor Sarah Smith
• Professor Fiona Steele
• Professor Kate Tilling
• Professor Frank Windmeijer

For other potential supervisors, please consult our academic staff pages on the relevant school websites.

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Entry requirements

A Masters (or equivalent qualification) in a discipline from the social or health sciences, and familiarity with intermediate-level quantitative techniques or multiple regression. For more methodological projects within the areas of social statistics and biostatistics, an MSc in Statistics or equivalent (eg Econometrics) is required.

For information on international equivalent qualifications, please see our International Office website.

Admissions statement

Read the programme admissions statement for important information on entry requirements, the application process and supporting documents required.

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Key research interests

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