Descripció i classificació de les comarques catalanes en regions homogènies segons l'ús de la terra
The theme of this article is the application of techniques of exploratory statistics to the study of comprehensive numerical tables consisting of statistics of a spatial nature. The immensity of statistics compiled over a large area, as in the case of a population census, frequently makes it difficu...
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 1986 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | catalán |
| OAI Identifier: | oai:upcommons.upc.edu:2117/103086 |
| Acceso en línea: | https://hdl.handle.net/2117/103086 |
| Access Level: | acceso abierto |
| Palabra clave: | Agriculture -- Statistics Mathematical statistics Agricultura -- Estadístiques Estadística matemàtica Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística aplicada |
| Sumario: | The theme of this article is the application of techniques of exploratory statistics to the study of comprehensive numerical tables consisting of statistics of a spatial nature. The immensity of statistics compiled over a large area, as in the case of a population census, frequently makes it difficult to assimilate all the information contained therein. It is shown that the mentioned techniques of analysis make possible a profound understanding of such statistics without resorting to the inspection of the said tables. The objectives usually pursued are: (1) to emphasize the most outstanding characteristics of the statistics, such as associations andlor contrasts in the elements under study, an objective which is easily fulfilled through methods of descriptive factorial analysis; (2) to group the basic elements of study into a limited number of representative classes, which can likewise be easily achieved through a simple algorithrn of ascendent hierarchical classification. The aplication of this method demonstrates the compatibility of the two results. This normally corresponds to the final stage in the study of statistical tables, in which observations relate to small areas points. The natural desire to make the classes obtained coincide with geographical regions made necessary the introduction of the content relationship within the algorithm of ascendent hierarchical classification. The application undertaken makes it possible to identify improvements in the interpretation of the classes obtained. |
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