cluster analysis

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clus·ter a·nal·y·sis

a set of statistical methods used to group variables or observations into strongly interrelated subgroups.
Farlex Partner Medical Dictionary © Farlex 2012

clus·ter anal·y·sis

(klŭstĕr ă-nali-sis)
Set of statistical methods used to group variablesor observations into strongly interrelated subgroups.
Medical Dictionary for the Health Professions and Nursing © Farlex 2012

cluster analysis

a statistical method of arranging a set of observations into sub-sets, each of which groups together those observations having similarities.
Collins Dictionary of Biology, 3rd ed. © W. G. Hale, V. A. Saunders, J. P. Margham 2005
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Therefore, cluster analyses are repeatedly carried out until the number of orbits in the optimal class is less than six.
However, the cluster analyses' results did not define decreasing tendencies in cluster distances among European countries because these distances were fluctuating during the analyzed period.
In the second part of our study, the convergence tendencies among member states of the European Union regarding taxation can be observed by comparing the results of successive cluster analyses. Table 1 presents the results of each cluster analysis in terms of determining the countries which have the most similar taxation systems.
Cluster analyses were performed with and without the demographic variables-gender, years of teaching, and highest degree earned.
Before any cluster analyses were conducted, general frequencies on demographic variables were calculated for the 26 couples (52 individuals) who participated in the experiments.
The Mann-Whitney U-test with Bonferroni correction was used to determine statistical significance between paired comparisons of clusters segregated by the threshold obtained from the results of cluster analyses.
Obviously, no manager would kno wingly analyse random data, but if data sets are not rigorously tested, the solutions from such cluster analyses (and other statistical techniques) can essentially be seen as devoid of meaningful structure.
Similarity coefficients were calculated by using the Dice algorithm, and cluster analyses were performed by the neighbor-joining algorithms by using the "Fuzzy Logic" and "Area Sensitive" option of the GelcomparII program.
Asked on cluster analyses of four dimensions of masculinity ideology, five patterns of endorsement were identified: moderately traditional, high status/low violence, nontraditional, high violence/moderately traditional.