Cluster Analysis

Date:

01/05/2015

Organised by:

University of Manchester

Presenter:

Dr Kitty Lymperopoulou

Level:

Entry (no or almost no prior knowledge)

Contact:

Short Courses Administrator; cmist-courses@manchester.ac.uk

Map:

View in Google Maps  (M13 9PL)

Venue:

The University of Manchester, Manchester M13 9PL
Humanities Bridgeford Building.

Description:

 

Outline

The course aims to cover cluster analysis concepts and methods that can be used to combine similar objects into groups or clusters. This course is aimed at those with an interest in developing practical skills to implement clustering techniques and those with an interest in geodemographic classifications.

Course Objectives

Participants will develop an understanding of cluster analysis methods and procedures in SPSS. By the end of the course they will be able to carry out preliminary analysis to select and transform variables to produce optimal cluster results, run cluster analysis in SPSS, select how many clusters are of interest, describe and interpret clusters and present cluster analysis results. Cluster analysis will be applied to Local Authority data to produce an area classification which groups areas with similar overall population characteristics into clusters.

Prerequisites

Participants should have a basic familiarity with SPSS and an understanding of basic data analytical techniques including correlation and regression analysis.

Recommended reading

M B. Everitt, S. Landau, M. Leese (2011) Cluster Analysis (5th Edition) Arnold, London 
J. Norušis M.J. (2011) IBM SPSS statistics 19 statistical procedures companion, Addison Wesley 
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.

Cost:

£195 (£140 for those from educational and charitable institutions)

Website and registration:

Region:

North West

Keywords:

Sampling , cluster , cluster analysis , regression analysis , correlation

Related publications and presentations:

Sampling

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