Using multivariate methods to determine the most important affecting factors for students' admission and their interests in the specializations: A sample of Salahaddin University

The main goal of this thesis is to determine the most important effective factors for student admission and his/her interests in the specialization by using multivariate methods. Therefore, it focused on using factor analysis by identifying a number of the obtained factors and cluster analysis by classifying the number of the clusters into five clusters. Furthermore, the results of the factor analysis and cluster analysis will be compared to each other. Moreover, this study depends on analysis of 350 questionnaire forms, which is distributed by random stratified sample method on students in the first stage of three different colleges include Scientific colleges and Humanity colleges of Salahaddin University in Northern Iraq for the academic year 2018-2019. Thus, the IBM SPSS Statistics V:25 software program has been used in data analysis. Additionally, the results have demonstrated that the reliability is accepted, and also in factor analysis the rate of the total variance interpretation is %62.157. Moreover, the most common variables between the factor analysis and cluster analysis can be considered the most important and influential variables for the student admission and their interests in choosing specialization. Consequently, the first factor and the first cluster have five influential variables in common, they are V1, V2, V3, V4 and V5 (the system is helpful for student admission in the colleges to get his/her desired professions). Ultimately, the conclusion has shown that there is a kind of approach and similarity between factor analysis and cluster analysis.