Classifying Syrian provinces according to householder spending using cluster analysis

This study aims to determine the difference of householder spending values between the Syrian provinces. It also aims to find out which of the components and the various items of expenditure, that contributed significantly to the occurrence of this difference and disparity between provinces , where cluster analysis method was used to find out this difference and classification . The most important results that have been reached: The result of cluster analysis is that there are three groups of Syrian provinces , the first group included the provinces of high householder spending such as Damascus province , the second group included the provinces of medium householder spending such as: Rural Damascus , Homs , Tartus , Lattakia , Al-Sweida , Daraa , Al – Quneitra . The third group included the provinces of low householder spending such as: Hama , Idleb , Aleppo , Al-Rakka , Deir-ez-Zor , Al-Hasakeh . Accordingly , that most important components and variables of householder spending, which contributed to the classification of the Syrian provinces of homogeneous groups are spending on housing , spending on education , spending on health , spending on transport and communications .

Using discriminating analysis of Classifying householders' spending in Syria during some economic factors

This study aimed at classifying householders' spending into three levels (high, moderate and low) and identifying which of the considered economic factors have a significant impact on the classification and which have not. In addition, this study aimed at deciding whether the suggested classifying model is statistically significant or not.

Studing the economic factors affecting consumer spending in Syria using factor Analysis

This study aimed at identifying the best indicators representing economic factors using Factor Analysis, as well as developing a mathematical model linking principal components which represent both the economic factors and consumer spending in Syria using Multi-linear regression analysis. A descriptive analytical approach is used in this study. The study results from Factor Analysis show that there are three principal components which best represent the economic factors. The first component includes: the number of workforce working for free, the number of paid workforce, consumer price index, the average annual GDP per capita. The second component includes: interest rate, self-employed workforce. The third component includes the number of employers. A mathematical model is developed to link the above three components of the economic factors and the total monthly household spending average in Syria during ( 2000-2010).

Studying the impact of social factors on household spending classification in Syria during (2000-2010)

This study aimed at using Multi-Variables Analysis in classifying household spending in Syria and identifying which of the social factors considered in the study influence significantly this classification and which do not. The most prominent results were: the possibility of classifying household spending into three levels (high, medium and low), there is a statistical significance of the factors (the percentage of urban population to total population, university education and above, number of married people and those in marriage age ) on the household spending classification. There is no statistical significance of the factors (educational levels below university education, non-married people, divorced or being widowed) on the household spending classification.