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Understanding small areas: spatial analysis of population and neighbourhood data
7th February 2019 - 8th February 2019
|Organised by||The University of Manchester|
|Presenter||Dr Alan Smith (University of Plymouth) & Dr Andy Newing (University of Leeds)|
|Date||07/02/2019 – 08/02/2019|
|Venue||Cathie Marsh Institute, HBS Building, Oxford Road Campus|
|Map||View in Google Maps (M139PL)|
|Contact||Claire Spencer, 0161 275 4579, email@example.com|
This two day workshop equips participants with conceptual understanding and technical skills to obtain, analyse and visualise spatial data related to populations and neighbourhoods. Using freely available data related to the UK, a series of guided workshops enable participants to:
Hands on training introduces participants to powerful spatial analysis software (ArcGIS) as well as the programming language R. Practical sessions are interspersed with lecture and discussions to contextualise and consolidate learning. Examples are drawn from the UK and are applicable in an international context and in a variety of application areas at different spatial scales.
Participants also have the chance to discuss their own related research or applications with other participants and the course tutors.
Population and neighbourhood data are widely used by the academic, policy-making and commercial sectors.
They drive resource allocation, decision making and policy evaluation. On completion of this course participants will be able to:
Additional reading material and web-based resources will be recommended during the course
|Level||Intermediate (some prior knowledge)|
For UK registered postgraduate students £30 per day
For staff at UK academic institutions, ESRC funded researchers and registered charity organisations £60 per day
For all other participants £220 per day
|Website and registration|
|Keywords||Qualitative Data Handling and Data Analysis, Mixed Methods Data Handling and Data Analysis|
|Related publications and presentations||Qualitative Data Handling and Data Analysis
Mixed Methods Data Handling and Data Analysis