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Using Cluster Analysis In Determining The Variables Affecting The Evaluation The Growth Of Children At Different Levels | ||
| journal of Economics And Administrative Sciences/ University of baghdad | ||
| Article 1, Volume 22, Issue 93, 2016, Pages 468-483 | ||
| Abstract | ||
| In light of the increasing interest in Child-rearing in nurseries and kindergartens and the most important experiences gained by the child at this stage that form the basis for the subsequent stages of her/his physical mental and social growth. The significance of the research concentrates the need to asses the affecting variables on the child growth to create opportunities for her/him to have intact rearing. The research also aims to classify these variables at each age level and highlight its moral role. The problem of the research is the lack of clarity of different variables impact of the child growth in different age levels in nurseries and kindergartens in the city of Sulaymaniyah. The research assumes that there are signs of the variables that have a significant relationship to assess the child's growth at every age levels. The research has adopted cluster analysis as one of multivariate analysis methods as it is characterized by working for classification, and the concentrated method has been used for classification of affected variables in children growth at different age levels and the use of detect the analysis factors in variables with high correlation at each age levels. The research found out that at the level age (3-4) years the variables of mental, emotional and social growth properties have clearly been saturated on many factors of this level and age level(4-5) years, depending on the factor analysis many saturated variables appeared as the characteristics of mental, physical and emotional growth properties. And at the level of age (5-6) years the mental and physical variables properties have been saturated and semi-completed compatibility emerged when both age levels (4-5)and (5-6) between variables saturation on the factors with compatibility in the cluster analysis results. | ||
| Keywords | ||
| luster analysis dendrogram; hierarchical cluster; centroied method; facter analysis; principle component method; The Kaiser; varimax | ||
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