MEIDATUZZAHRA, DIAH (2017) POPULATION ANALYSIS OF DISABLED CHILDREN BY DEPARTMENTS IN FRANCE. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
In this study, a statistical analysis is performed by model the variations of the disabled about 0-19 years old population among French departments. The aim is to classify the departments according to their profile determinants (socioeconomic and behavioural profiles). The analysis is focused on two types of methods: principal component analysis (PCA) and multiple correspondences factorial analysis (MCA) to review which one is the best methods for interpretation of the correlation between the determinants of disability (independent variable). The hierarchical cluster analysis (HCA) can be used to classify the departments according to their profile determinants. Analysis of variance or ANOVA is performed to know difference the between cluster and within cluster variances of two proxy data (AEEH and EN3-EN12). The PCA reduces 14 determinants of disability to 4 axes, keeps 80% of total information, and classifies them into 7 clusters. The MCA reduces the determinants to 3 axes, retains only 30% of information, and classifies them into 4 clusters. The ANOVA of the proxy data by department cluster are difference significant between cluster and the variance within of cluster is not difference significant, the cluster are homogeneous.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Disability of Children, Principal component analysis, Multiple Coresspondences Analysis, Hierarchical Cluster Analysis, Analysis of Variance |
| Subjects: | Q Science Q Science > QA Mathematics > QA278 Cluster Analysis. Multivariate analysis. Correspondence analysis (Statistics) |
| Divisions: | Faculty of Mathematics and Science > Statistics > 49101-(S2) Master Thesis |
| Depositing User: | DIAH MEIDATUZZAHRA |
| Date Deposited: | 24 Jan 2017 04:50 |
| Last Modified: | 06 Mar 2019 02:53 |
| URI: | http://repository.its.ac.id/id/eprint/2928 |
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