china conference

ESRC Summer School: Analysing Segregation

Applied Statistical Methods for Analysing Segregation & Inequality

1-4 August 2017, The University of Sheffield

About the Summer School

Significant advances in the measurement and analysis of segregation have been made over the past 5 years. This summer school offers delegates the opportunity to learn these cutting-edge methods from leading researchers in the field.

The summer school will provide 4 days of intensive hands-on training, providing an intensive introduction to measuring and modelling segregation. Participants will gain an understanding of, and develop their skills in, the following four topics:

1. Introduction to R – reading in data, plotting data, variables and subsetting, data manipulation and management, numerical summaries, reading in shape files, drawing maps of areal unit data.
2. Spatial analysis of segregation – techniques for spatial aspects of segregation, how to compute inference for segregation indices including index of dissimilarity, and analysis of the spatial persistence of migrants.
3. Multiscale Segregation – multilevel modelling of segregation and inequality to capture the different levels of segregation at different spatial scales.
4. Clusters and Frontiers in Social Relations: new ways of thinking of segregation through the application of Social Network Analysis, social frontier estimation and modelled cluster methods to issue of segregation.

Speakers

We have an outstanding set of trainers and speakers including:

Dr Nema Dean (University of Glasgow) – statistician with expertise in social network analysis and cluster modelling; and pioneer in the development of perceived substitutability approaches to segregation using social network analysis.
Dr Guanpeng Dong (University of Liverpool) – quantitative geographer and winner of the John Rasbash Prize for social statisics for the development of spatial multilevel estimation methods.
Dr Duncan Lee (University of Glasgow) – leading expert in spatial analysis, and pioneer in the development of inference for segregation measurement.
Dr David Manley (University of Bristol) – quantitative geographer and pioneer of the multilevel modelling approach to multi-scale segregation measurement.
Dr Aneta Piekut (University of Sheffield) – Q-Step lecturer and award-winning researcher with expertise in social diversity, attitudes and prejudice, ethnic minorities’ integration, and socio-spatial segregation.
Prof Gwilym Pryce (University of Sheffield) - leader of the Urban Segregation and Inequality ESRC AQMeN research project, and co-author on the development of inference for segregation and perceived substitutability measures of segregation.

Who is the Summer School for?

This course is aimed at researchers interested in the quantitative analysis of segregation using the latest methods. The course is open to academics, postgraduate students and researchers outside of academia interested in improving their skills in this area. Most of the course will be taught in R and other freely available software. No prior knowledge of R is required, but you should have a good knowledge of introductory statistics and regression analysis – see “how to apply” below. Lunch and some evening meals will be provided.

The course will be preceded by a one-day conference on segregation in Europe and China hosted by the University of Sheffield to which you are warmly invited. For further details email amy.clare@sheffield.ac.uk.

Both the conference and the Summer School are funded by the ESRC in collaboration with the Sheffield Methods Institute.

Schedule

Day 1
Theory and Intro to R
9.45 to 17.30

Day 2
Spatial Analysis and Segregation Measurement Using CARBayes
9.15 to 17.30

Day 3
Multilevel Approaches to Segregation
9.15 to 17.30 followed by Evening Dinner

Day 4
Social Frontiers, Clusters and Networks
9.15 to 16.00

Download full schedule 

How to apply

Applicants will need to have a good knowledge of introductory statistics up to and including linear regression analysis. Experience of using R and/or other syntax based statistics software is also desirable but not essential. Proficiency in written and verbal English is also a prerequisite.

Places are limited so applications will be judged on merit. 

Applications are now closed.