Using Cluster Analysis and Discriminant Analysis Methods in Classification with Application on Standard of Living Family in Palestinian Areas
Mo'oamin M. R. El-Hanjouri, Bashar S. Hamad · International journal of statistics and applications · 2015
This research applied methods of multivariate statistical analysis, especially cluster analysis (CA) in order to recognize the disparity in the living standards for family among the Palestinian areas. The research results concluded that there is a convergence in living standards for family between two areas formed the first cluster of high living standards which are the urban of middle West Bank and the camp of middle West Bank, also there was a convergence of living standards for family among the seven areas formed the second cluster of middle living standards which are the urban of North West Bank, the camp of North West Bank, the rural of North West Bank, the urban of South West Bank, the camp of South West Bank, the rural of South West Bank and the rural of middle West Bank. In addition, there is a convergence of living standards for family among the three areas formed the third cluster of low living standards which are the urban of Gaza strip, the rural of Gaza strip and the camp of Gaza strip. After a comparison among several methods of cluster analysis through a cluster validation (Hierarchical Cluster Analysis, K-means Clustering and K-medoids Clustering), the preference was for the Hierarchical Cluster Analysis method. However, after an examination to choose the best method of connection through agglomerate coefficient in the Hierarchical Cluster Analysis (Single linkage method, Complete linkage method, Average linkage method and Ward linkage method), the preference was for Ward linkage method which has been selected to be used in the classification. Moreover, the Discriminant Analysis method (DA) applied to distinguish the variables that contribute significantly to this disparity among families inside Palestinian areas and the results show that the variables of monthly Income, assistance, agricultural land, animal holdings, total expenditure, imputed rent, remittances and non-consumption expenditure are significantly contributed to disparity. Keywords Cluster Analysis (CA), Hierarchical Cluster Analysis (HCA), Discriminant Analysis (DA)