Use of multivariate statistical techniques in profiling and segmentation.
Objective.To use the information about the factors identified, by means of correspondence analyses to determine the behavior of the variables to be used to then make a natural segmentation, thus facilitating the interpretation and presentation of results. Materials and methods. We present a new...
| Autor Principal: | Rueda Varon, Milton Januario; Grupo de Física Matemática. Facultad de Ciencias, Pontificia Universidad Javeriana, Bogotá, D.C., Colombia. |
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| Otros Autores: | Moya-Moya, Luz Marina; Departamento de Matemáticas. Facultad de Ciencias, Pontificia Universidad Javeriana, Bogotá, D.C., Colombia., Aranda-Silva, Moises; Departamento de Matemáticas. Facultad de Ciencias, Pontificia Universidad Javeriana, Bogotá, D.C., Colombia. |
| Formato: | info:eu-repo/semantics/article |
| Idioma: | eng |
| Publicado: |
Pontificia Universidad Javeriana
2011
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| Materias: | |
| Acceso en línea: |
http://revistas.javeriana.edu.co/index.php/scientarium/article/view/1797 |
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| Sumario: |
Objective.To use the information about the factors identified, by means of correspondence analyses to determine the behavior of the variables to be used to then make a natural segmentation, thus facilitating the interpretation and presentation of results. Materials and methods. We present a new profiling and segmentation approach by using correspondence analyses and classification. Results. By using this methodology we can optimize the determination of segments and the profiling of a set of variables. This procedure allows researchers of different disciplines to present and interpret the results of their research efficiently. Conclusions. The procedure here described enables a simple and quick interpretation of the analysis on many variables, rendering its use and implementation easy. Key words: profiling, segmentation, multivariate techniques, correspondences. |
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