Oxford Spring School in Advanced Research Methods

Date:

27/03/2017 - 31/03/2017

Organised by:

University of Oxford

Presenter:

Professor Elias Dinas
Professor Ezequiel González-Ocantos
Professor Andrea Ruggeri

Level:

Intermediate (some prior knowledge)

Contact:

Margo Kirk, Oxford Spring School Administrator
springschool@politics.ox.ac.uk
+44 1865 278703

Map:

View in Google Maps  (OX1 3UQ)

Venue:

Department of Politics and International Relations
Manor Road Building
Manor Road
Oxford
OX1 3UQ

Description:

The Oxford Spring School in Advanced Research Methods offers graduate students and researchers from universities across the UK and abroad a unique venue to learn cutting-edge methods in quantitative and qualitative methods in the social sciences, with a variety of advanced courses which place the different data analysis techniques within broader disciplinary trends towards mixed-methods research designs.

Funding

We are delighted to be able to offer five full bursaries and six half bursaries. Offers will be made on merit.

Course Options

Course options include a choice between sets of increasingly popular and influential methods/techniques in the discipline:

·         Social Network Analysis  

·         Causal Inference

Other options will be:

·         Process Tracing

·         Forecasting

·         Spatial Analysis

·         Data Visualisation

Participants will be able to take a total of up to three different methods courses in one week, as well as a masterclass session on how to publish their research in peer-reviewed journals. Tutors will emphasise the mixed-methods philosophy underlying these courses, and the use of these techniques in different types of research designs.

Registration deadline: Monday 16 January 2017

Cost:

£650

Website and registration:

Region:

South East

Keywords:

Explanatory Research and Causal analysis, Mixed Methods, Statistical Theory and Methods of Inference, Spatial Data Analysis, Forecasting, Social Network Analysis, R, Data Visualisation

Related publications and presentations:

Explanatory Research and Causal analysis
Mixed Methods
Statistical Theory and Methods of Inference
Spatial Data Analysis
Forecasting
Social Network Analysis
R
Data Visualisation

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