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The k-means algorithm is a clustering method which measures the proximity between groups using the Euclidean distance between group centroids. Beginning with an initial selection of k groups, this clustering algorithm allows to locate each respondent within clusters according to his/her distance to the nearest centroid. In total, 10 cluster solutions were tested using the Environics 1995 survey data. A scree plot of the derived proximity measure (in this case the Euclidean distance between group centroids) by the cluster solution is presented in chart 1.  1, fiche 1, Anglais, - group%20centroid

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