A Monte Carlo Approach to Estimating the Significance of Segregation

Bibliographic Data

ID5086089
AuthorsAnne Findlay (0000-0003-1002-4391, University of Glasgow)
Year1984
Volume16
Issue2
Pages225-231
Publication date1984-02-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEnvironment and Planning A Economy and Space (JOURNAL)
Journal identifiersISSN: 0308-518X • E-ISSN: 1472-3409
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1068/a160225
OpenAlexW2023788739
LanguageEN
Citations received4
References cited16

Simulation techniques are not new to geography, but they have focused traditionally on attempts to replicate observed patterns rather than on seeking to assist in the formulation of a null hypothesis. The benefits and problems of a Monte Carlo simulation methodology are examined with reference to the latter objective. The flexibility of the approach in the evaluation of spatial statistics is shown to be considerable. Specific case studies are pursued which exemplify its potential in the investigation of social segregation using familiar measures such as the dissimilarity index and the P* index

Data mining · Econometrics · Monte Carlo method · Null hypothesis · Physics · Replicate · Statistical physics · Statistics · Computer Science · Mathematics · Regional Economics and Spatial Analysis · Spatial and Panel Data Analysis · Urban, Neighborhood, and Segregation Studies

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