Creating a typology of parishes in England and Wales: Mining 1881 census data

The paper presents the application of principal component analysis and cluster analysis to historical individual level census data in order to explore social and economic variations and patterns in household structure across mid-Victorian England and Wales. Principal component analysis is used in or...

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Main Authors: Kevin Schürer, Tatiana Penkova
Format: Article
Language:English
Published: International Institute of Social History 2015-09-01
Series:Historical Life Course Studies
Subjects:
Online Access:https://test.openjournals.nl/hlcs/article/view/9358
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author Kevin Schürer
Tatiana Penkova
author_facet Kevin Schürer
Tatiana Penkova
author_sort Kevin Schürer
collection DOAJ
description The paper presents the application of principal component analysis and cluster analysis to historical individual level census data in order to explore social and economic variations and patterns in household structure across mid-Victorian England and Wales. Principal component analysis is used in order to identify and eliminate unimportant attributes within the data and the aggregation of the remaining attributes. By combining Kaiser’s rule and the Broken-stick model, four principal components are selected for subsequent data modelling. Cluster analysis is used in order to identify associations and structure within the data. A hierarchy of cluster structures is constructed with two, three, four and five clusters in 21-dimensional data space. The main differences between clusters are described in this paper.
format Article
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institution Kabale University
issn 2352-6343
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publishDate 2015-09-01
publisher International Institute of Social History
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series Historical Life Course Studies
spelling doaj-art-119aca913d5f4cae90b2f61eef2f13ef2025-02-02T13:57:18ZengInternational Institute of Social HistoryHistorical Life Course Studies2352-63432015-09-012Creating a typology of parishes in England and Wales: Mining 1881 census dataKevin SchürerTatiana PenkovaThe paper presents the application of principal component analysis and cluster analysis to historical individual level census data in order to explore social and economic variations and patterns in household structure across mid-Victorian England and Wales. Principal component analysis is used in order to identify and eliminate unimportant attributes within the data and the aggregation of the remaining attributes. By combining Kaiser’s rule and the Broken-stick model, four principal components are selected for subsequent data modelling. Cluster analysis is used in order to identify associations and structure within the data. A hierarchy of cluster structures is constructed with two, three, four and five clusters in 21-dimensional data space. The main differences between clusters are described in this paper.https://test.openjournals.nl/hlcs/article/view/9358Household structuresCensus dataCluster analysisPrincipal component analysis
spellingShingle Kevin Schürer
Tatiana Penkova
Creating a typology of parishes in England and Wales: Mining 1881 census data
Historical Life Course Studies
Household structures
Census data
Cluster analysis
Principal component analysis
title Creating a typology of parishes in England and Wales: Mining 1881 census data
title_full Creating a typology of parishes in England and Wales: Mining 1881 census data
title_fullStr Creating a typology of parishes in England and Wales: Mining 1881 census data
title_full_unstemmed Creating a typology of parishes in England and Wales: Mining 1881 census data
title_short Creating a typology of parishes in England and Wales: Mining 1881 census data
title_sort creating a typology of parishes in england and wales mining 1881 census data
topic Household structures
Census data
Cluster analysis
Principal component analysis
url https://test.openjournals.nl/hlcs/article/view/9358
work_keys_str_mv AT kevinschurer creatingatypologyofparishesinenglandandwalesmining1881censusdata
AT tatianapenkova creatingatypologyofparishesinenglandandwalesmining1881censusdata