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Cathie Marsh Institute for Social Research (CMI)

Introduction to Cluster Analysis

Date: 1 February 2019
Time: 10am – 4.30pm
Instructor: Kitty Lymperopoulou
Level: Introductory
Fee: £195 (£140 for those from educational, government and charitable institutions). 

We offer up to 5 subsidised places at a reduced rate of £60 per course day to research staff and students within Humanities at the University of Manchester. These places are awarded in order of application. 

Humanities PGR students at The University of Manchester can apply for a methods@manchester bursary to help cover their costs. All applications will be considered on a case-by-case basis and applicants will be required to provide a supporting statement from their supervisor.

Please contact Joshua Edgar (email: methods@manchester.ac.uk) for an application form and further information.

Please note: This is not guaranteed and is considered on a case by case basis. Please contact us for more information.

Outline

The course covers cluster analysis concepts and methods. It is aimed at those with an interest in developing practical skills to implement clustering techniques and those with an interest in area typologies and classifications.

Course objectives

Participants will develop an understanding of clustering methods and procedures, carrying out analysis in the program 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, interpret clusters and present cluster analysis results. Hierarchical and non-hierarchical cluster analysis will be applied to 2011 Census local area data to produce an area classification to group areas with similar overall population characteristics into clusters.

Prerequisites

Participants should have familiarity with statistical software and an understanding of basic data analysis techniques including correlation and regression analysis. 

Recommended reading

  • M B. Everitt, S. Landau, M. Leese (2011) Cluster Analysis (5th Edition) Arnold, London
  • Vickers, D., and Rees, P. (2007). Creating the national statistics 2001 output area classification, Journal of the Royal Statistical Society, Series A 170 (2), pp. 379–403.

About the instructors

Apply

Participants will develop an understanding of clustering methods and procedures, carrying out analysis in the program 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, interpret clusters and present cluster analysis results. Hierarchical and non-hierarchical cluster analysis will be applied to 2011 Census local area data to produce an area classification to group areas with similar overall population characteristics into clusters.