Advanced Quantitative MethodsFind a programme
|Run by||Faculty of Social Sciences and Law|
Four years full-time;
seven years part-time
|Location of programme||Clifton campus|
|Part-time study available||Yes|
|Open to international students||Yes|
|Number of places||Not fixed|
|Start date||September 2017|
This 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 who are interested in inter-disciplinary research that requires the application of quantitative methods from one discipline to problems in another.
This 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.
Fees for 2017/18
Fees quoted are provisional, per annum and subject to annual increase.
Funding for 2017/18
The Faculty of Social Sciences and Law has an allocation of 1+3 and +3 ESRC scholarships. Applicants may also be interested in applying for funding from the University of Bristol scholarship fund and alumni PhD scholarship fund.
Further information on funding for prospective UK, EU and international postgraduate students.
A Master's (or equivalent) in a discipline from the social or health sciences, and familiarity with intermediate-level quantitative techniques or multiple regression. For more methodological projects within social statistics and biostatistics, an MSc in Statistics or equivalent (eg econometrics) is required.
See international equivalent qualifications on the International Office website.
|Application method||Online application form|
|English language requirements||
Further information about English language requirements
|Admissions statement||Read the programme admissions statement for important information on entry requirements, the application process and supporting documents required.|
The ESRC has designated advanced quantitative methods as a priority area, and the purpose of this pathway is to provide training and supervision that emphasises quantitative methods to a higher level than is usually offered. Training includes a structured programme of core advanced quantitative methods courses and a fortnightly research and reading group.
Details of the core training currently offered can be found on the advanced quantitative methods courses website.
Key research interests
You will need two supervisors: one supervisor with advanced quantitative methods expertise and one supervisor with expertise in your chosen substantive area. Your main supervisor must be from a social science discipline. For a list of potential supervisors, please consult our academic staff pages on the relevant school websites.
Our students go on to employment in a wide variety of areas - often where statistical analysis is required, but also where numeracy is crucial. Students also continue within academic careers, going on to postdoctoral and lecturing positions.
At its core, the programme establishes a sound research training base, together with a set of bespoke training courses that provide students with the advanced quantitative toolkit required for their PhD research. It also positions our students for different types of employment, including research, policy and intervention implementation.
Dr Malcolm Fairbrother, (Senior Lecturer, Research Fellow), Macro-social determinants of individual level outcomes; relationships between political economy and the natural environment; social change.
Dr Rich Harris, (Professor), Methodological interests in spatial statistics, spatial econometrics, GIS and geodemographics; spatial measures of inequality and segregation; the geographies of education under systems of choice.
Professor Kelvyn Jones, (Professor), Geography of health: geographical inequalities in mortality in advanced economies; realistically complex modelling: the quantitative analysis of social science data; research design: developing evidence-based research in non-experimental studies.
Dr George Leckie, (Senior Lecturer), Longitudinal data analysis and dyadic data analysis; multilevel analysis of non-hierarchical data; the application and dissemination of multilevel and other latent variable models to analyse educational and social science data.
Dr David Manley, (Senior Lecturer), Segregation: multiple approaches to measuring and analysing; urban geography: urban inequalities, integration of the life course into static models.
Professor Clive Sabel, (Chair in Quantitative Geography), Environmental and social exposure; health geography; social deprivation and inequalities.
Professor Sarah Smith, (Professor, Head of Department), Analysis of the effects of policy reform; intergenerational transmission; modelling individual behaviour, including fertility, health, retirement, charitable giving and subjective well-being.
Professor Kate Tilling, (Professor), Childhood growth; complex interrelationships which change over time (eg. fat mass and physical activity, risk factors for CHD); lifecourse analyses; trajectories of change in disease outcomes.
Dr Liz Washbrook, (Lecturer), Relationships between family background, policy and early childhood outcomes and methodological issues in the analysis of longitudinal data.
Professor Frank Windmeijer, (Professor), Demand for health and health care; policy evaluation; using genetic markers in social science research.
Not fixed but early application is advised. Deadlines for funded applications are likely to be in February.
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REF 2014 results
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School of Geographical Sciences
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