Introduction to Cluster Analysis
| Dates: | 30 April 2020 |
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| Times: | All day |
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| What is it: | Short course |
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| Organiser: | Cathie Marsh Institute for Social Research |
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| How much: | £195
/ £140
/ Five subsidised £60 places available for Humanities staff and postgraduates |
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| Who is it for: | University staff, External researchers, Alumni, Current University students |
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| Speaker: | Kitty Lymperopoulou |
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Outline
The course covers basic ideas and concepts in cluster analysis including hierarchical and non-hierarchical clustering methods and their application. Throughout the day, participants will have guided practicals in R using ecological data from the UK Census of population on how to choose and transform variables for cluster analysis, how to perform cluster analysis using different clustering techniques, and how to examine cluster results and cluster validity.
Course objectives
Basic ideas and concepts of hierarchical and non-hierarchical cluster analysis
Selection of variables for cluster analysis
Choice and application of an appropriate clustering technique in R
Determine an optimal cluster solution
Cluster interpretation
Cluster validation
Participants will develop an understanding of clustering methods and procedures, carrying out analysis in R. By the end of the course, they will be able to carry out preliminary analysis to select and transform variables for cluster analysis, choose a clustering method, evaluate and choose cluster solutions, and interpret cluster results.
The course will enable participants to develop practical skills to implement clustering techniques to identify structures or groupings within data, to better understand social, economic and spatial dimensions of populations, and categorise data for further analysis, for example for statistical modelling or in-depth case study research.
Price: £195
Concessions: £140
Offers: Five subsidised £60 places available for Humanities staff and postgraduates
Travel and Contact Information
Find event
Basement Lab
Humanities Bridgeford Street
Manchester
