التحليل الإحصائي متعدد المتغيرات (التحليل التمييزي) (في توصيف و توزيع الأسر داخل الهيكل الاقتصادي الاجتماعي في المجتمع)

يتضمن هذا البحث دراسة أحد أساليب التحليل الإحصائي متعدد المتغيرات هو أسلوب التحليل التمييزي الذي يعد من الأساليب الإحصائية المتقدمة التي تستخدم في توصيف و توزيع الأسر داخل الهيكل الاقتصادي الاجتماعي للمجتمع، و يساعد في رسم خطط التنمية الاقتصادية و الاجتماعية التي تهدف إليها الدولة و الوقوف على أنسب الطرائق من حيث عدالة توزيع الدخل و العبء الضريبي و الإعانات الحكومية لأسر المجتمع بصورة أكثر واقعية. يطبق هذا الأسلوب من خلال عدة متغيرات تُحدد من قبل الباحث من أجل الوصول إلى الأهداف الآتية: توصيف و توزيع الأسر داخل الهيكل الاقتصادي للمجتمع. تحديد العوامل و المتغيرات التي تؤثر في توصيف و توزيع الأسر داخل الهيكل الاقتصادي الاجتماعي في المجتمع. محاولة تطوير أساليب و تقانات التحليل الإحصائي و تطبيقها في الدراسات الاقتصادية.

The Discriminant Analysis of the Responses of a Sample of University Students to Of the Authentic Happiness List

The aim of current research on detection of discriminatory ability to Authentic Happiness list to the responses of a sample of university students, the research sample consisted of sample of the student collectors have numbered 419 students, including (125) males and (294) females.

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.

The Effectiveness Discriminating of the Part One of the Adaptive Behavior Scale in Discrimination Between the Ages - Field Study One Sample of Children in Damascus Governorate Schools

This research aimed to identify the discrimination capacity of the part one of AAMR adaptive behavior scale in discrimination between children from different ages, through studying the differences between children's performance who including in the research, where the research sample consisted of (490) children aged (11-15) year, they are students in the second stage basic teaching students in Damascus governorate schools.

The Effectiveness Discriminating of the Part One of the Adaptive Behavior Scale in Discrimination Between the Ages - Field Study One Sample of Children in Damascus Governorate Schools

This research aimed to identify the discrimination capacity of the part one of AAMR adaptive behavior scale in discrimination between children from different ages, through studying the differences between children's performance who including in the research, where the research sample consisted of (490) children aged (11-15) year, they are students in the second stage basic teaching students in Damascus governorate schools.

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.

Evaluating The Private Banking Sector Performance Depending On CAMELS: Applied Study On Private Banks Listed In Damascus Stock Market

The research aimed to assess the performance of the private banking sector in Syrian Arab Republic during the period between 2010-2018 from a supervisory prospect of the Central Bank to determine the strengths and weaknesses of the banking sector in Syrian Arab Republic. We gathered the statistical data issued by local banks (14 traditional and Islamic banks). The performance of the banks was evaluated separately using the CAMELS model, where the study showed average performance of the operating banks. The researchers deliberately used indicators of capital adequacy, asset quality, management efficiency, profitability, liquidity, and sensitivity to market risks. In addition, the researchers tried to study the effect of stock market risk on the performance of the banking sector by forming a portfolio of shares of banks operating in Syria. The results of the statistical analysis using the SPSS program, through the Discriminant Analysis test, showed the presence of an impact of a number of indicators on the performance of the banking sector. In the end, a model for evaluating the performance of the banking sector was obtained using a multiple regression model and the model is able to explain the performance of the banking sector by 88.4%.