Aplicação de técnica estatística multivariada em indicadores de sustentabilidade nos municípios do Marajó-PA
Indicators are important tools to guide and assist decision-makers. They are also important to get to know the scenario of a given place and monitor its development. This study aimed to analyze the behavior of the municipalities of Marajó-PA through indicators that cover social, economic, housing an...
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| Published in: | Revista Principia Vol. 1; no. 46; pp. 145 - 154 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Instituto Federal de Educação, Ciência e Tecnologia da Paraíba
30-09-2019
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| Subjects: | |
| Online Access: | Get full text |
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| Summary: | Indicators are important tools to guide and assist decision-makers. They are also important to get to know the scenario of a given place and monitor its development. This study aimed to analyze the behavior of the municipalities of Marajó-PA through indicators that cover social, economic, housing and sanitation, using a statistical technique of multivariate analysis to group these into a small number of homogeneous groups. In order to choose the indicators, we carried out a checklist of national, regional and local academic papers dealing with sustainability. Then, the indicators were standardized according to the different units and scales of measurement, not influencing the result and presenting similar weights in the calculation of the similarity coefficient. The measure of dissimilarity used was the euclidean distance and for the composition of the groupings the Ward and k-Means methods were applied. The result obtained using Ward’s hierarchical grouping method enabled the reduction of the numbers of municipalities to a number of 4 probable groups with similar attributes within the group and distinct among the others. It also presented a cofenetic correlation coefficient (CCC) of (r = 0.81), indicating a good degree of fit between the dendrogram and the dissimilarity matrix. The results indicated that the formation of the clusters and the municipalities integrated in them presented similarity both in the hierarchical and non-hierarchical methods. In the k-means method it was found that almost all municipalities that make territorial division remained within the same group. |
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| ISSN: | 1517-0306 2447-9187 |
| DOI: | 10.18265/1517-03062015v1n46p145-154 |