Employment of Cluster Analysis to Study the Classification Variables for the Youth Development in Iraq - Mahdi Ahmed, Huda; Hameed Mahmood, Amenah (International Journal of Psychosocial Rehabilitation, 2020)
Cluster analysis is one of the branches of multivariate statistical analysis. It is a set of procedures that seeks to classify the sample of observations into two or more dependent categories, depending on the combinations of the variables categories, for discovering common characteristics to organize the views (individuals) and dividing them into groups with the same characteristics. The young people are the cause of the rise of the nations, the secret of their strength. Therefore, the effective role played by the state in the development of societies is to create mentally and scientifically qualified young people to serve their country and society with appropriate solutions. In this study we used two different types of clustering analysis methods, hierarchical and k-means, and used the classification from two to four groups. So, it was concluded that the Iraqi cities were classified into four groups depending on some variables of youth development in Iraq. Moreover, the cities of the second group are characterized by the highest rate of economic activity, while the cities of the third group have the highest rate of literacy, the cities of the first group have the highest rate of food insecurity, and the cities of the fourth group have the highest rate of youth who have the best health.