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.

The Impact of Information Technology Use on the Performance of Tishreen University Students using Discriminant Analysis

This study aimed at identifying the impact of information technology use on the student's performance amongst Tishreen University faculties, and identifying which factors relate to information technology use have contributed to the differences and variations in student's performance. Consequently, developing a mathematical model for classifying students' performance using discriminant analysis. The most important findings of this research are: There is a significant classification impact of the availability of the following factors: sources and scientific references, computing laboratories, the Internet, computing curriculum, tutors followed training courses in student's performance classification. The findings showed that there is no significant classification impact of the following two factors: foreign language proficiency and the availability of data show facilities on the student's performance classification. In addition, three discriminant functions are obtained which reflect student's performance. Furthermore, the developed model classified studied sample members correctly with 70.2%, which reflect a significant impact of the developed model on classifying student's performance.

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.