[ Analyse des composantes principales : cas d'un échantillon des prestataires logistiques de la région du grand Casablanca ]
Volume 11, Issue 2, November 2014, Pages 371–378
Moulay El Mehdi Falloul1
1 Ph.D candidate in applied economics and finance, Hassan II University of Mohammedia, Mohammedia, Morocco
Original language: French
Copyright © 2014 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The principal component analysis, introduced by Hotelling in 1933, is a descriptive method which is aimed at the analysis of the data tables which does not have a particular structure, in other words, comments at first glance with no distinction between variables, or between individuals. The PCA aims to summarize information contained in an array consisting of large number of rows and columns, a few graphs in two dimensions, and more a number of digital features. We will use this method to analyze a sample of logistics service providers in the region of the great Casablanca in Morocco.
Author Keywords: Principal component analysis, random sample, logistics service providers, explained variance, component diagram.
Volume 11, Issue 2, November 2014, Pages 371–378
Moulay El Mehdi Falloul1
1 Ph.D candidate in applied economics and finance, Hassan II University of Mohammedia, Mohammedia, Morocco
Original language: French
Copyright © 2014 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
The principal component analysis, introduced by Hotelling in 1933, is a descriptive method which is aimed at the analysis of the data tables which does not have a particular structure, in other words, comments at first glance with no distinction between variables, or between individuals. The PCA aims to summarize information contained in an array consisting of large number of rows and columns, a few graphs in two dimensions, and more a number of digital features. We will use this method to analyze a sample of logistics service providers in the region of the great Casablanca in Morocco.
Author Keywords: Principal component analysis, random sample, logistics service providers, explained variance, component diagram.
Abstract: (french)
L'analyse en composante principale, introduite par Hotelling en 1933, est une méthode descriptive qui a pour but l'analyse des tableaux des données qui ne présente pas une structure particulière, autrement dit, des observations ne comportant à priori aucune distinction, ni entre variables, ni entre individus. L'objectif de l'ACP est de résumer l'information contenue dans un tableau constitué de nombre élevé de lignes et de colonnes, en quelques représentations graphiques à deux dimensions, plus un certain nombre de caractéristiques numériques. Nous allons utiliser cette méthode pour analyser un échantillon des prestataires logistiques de la région du grand Casablanca au Maroc.
Author Keywords: Analyse en composante principale, échantillon aléatoire, prestataires logistiques, variance expliquée, diagrammes des composantes.
How to Cite this Article
Moulay El Mehdi Falloul, “Principal component analysis : case of a sample of logistics service providers of the great Casablanca region,” International Journal of Innovation and Scientific Research, vol. 11, no. 2, pp. 371–378, November 2014.
