HİYERARŞİK KLUSTER (KÜME)TEKNİĞİ KULLANILARAK TÜRKİYE’DE İLLERİN SOSYO-EKONOMİK BENZERLİKLERİNİN ANALİZİ
In this study, 54 socio-economic variables were used to determine groups for Turkish provinces which represent similar characteristics. To achive this goal hierarchical cluster analyses was decided to be an appropirate statistical test. While doing determination of number of clusters for 81 province...
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| Format: | Article |
| Language: | English |
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Ankara University
2004-08-01
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| Series: | Coğrafi Bilimler Dergisi |
| Subjects: | |
| Online Access: | https://dergipark.org.tr/tr/pub/aucbd/issue/44490/551499 |
| _version_ | 1797832981136539648 |
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| author | Murat KARABULUT Mehmet GÜRBÜZ Ersin Kaya SANDAL |
| author_facet | Murat KARABULUT Mehmet GÜRBÜZ Ersin Kaya SANDAL |
| author_sort | Murat KARABULUT |
| collection | DOAJ |
| description | In this study, 54 socio-economic variables were used to determine groups for Turkish provinces which represent similar characteristics. To achive this goal hierarchical cluster analyses was decided to be an appropirate statistical test. While doing determination of number of clusters for 81 provinces, the data set was tested with 7,10 and 15 clusters(groups). As a result of testing clustering processes, the group with 15 members was selected to use during analyses. The analyses were supported with dendogram and agglomerative schedule. Squared oklid distance and pearson proximity matrix were used to calculate distances between different provinces to find out province groups which have similar socio-economic character. The results indicate that, the most similar provinces are Bitlis and Mardin, and the least similar provinces are İstanbul and Kars. Consequently, this study is able to determine social and economical differences of Turkey’s provinces with aid of hierarchical cluster technique |
| first_indexed | 2024-04-09T14:16:25Z |
| format | Article |
| id | doaj.art-89ee0423c1094eb2992368f5ac070175 |
| institution | Directory Open Access Journal |
| issn | 1303-5851 1308-9765 |
| language | English |
| last_indexed | 2024-04-09T14:16:25Z |
| publishDate | 2004-08-01 |
| publisher | Ankara University |
| record_format | Article |
| series | Coğrafi Bilimler Dergisi |
| spelling | doaj.art-89ee0423c1094eb2992368f5ac0701752023-05-05T07:18:30ZengAnkara UniversityCoğrafi Bilimler Dergisi1303-58511308-97652004-08-0122657810.1501/Cogbil_0000000043HİYERARŞİK KLUSTER (KÜME)TEKNİĞİ KULLANILARAK TÜRKİYE’DE İLLERİN SOSYO-EKONOMİK BENZERLİKLERİNİN ANALİZİMurat KARABULUT 0Mehmet GÜRBÜZ 1Ersin Kaya SANDAL2KSÜ Fen-Edebiyat Fakültesi, Coğrafya Bölümü, Kahraman Maraş KSÜ Fen-Edebiyat Fakültesi, Coğrafya Bölümü, Kahraman MaraşKSÜ Fen-Edebiyat Fakültesi, Coğrafya Bölümü, Kahraman Maraş In this study, 54 socio-economic variables were used to determine groups for Turkish provinces which represent similar characteristics. To achive this goal hierarchical cluster analyses was decided to be an appropirate statistical test. While doing determination of number of clusters for 81 provinces, the data set was tested with 7,10 and 15 clusters(groups). As a result of testing clustering processes, the group with 15 members was selected to use during analyses. The analyses were supported with dendogram and agglomerative schedule. Squared oklid distance and pearson proximity matrix were used to calculate distances between different provinces to find out province groups which have similar socio-economic character. The results indicate that, the most similar provinces are Bitlis and Mardin, and the least similar provinces are İstanbul and Kars. Consequently, this study is able to determine social and economical differences of Turkey’s provinces with aid of hierarchical cluster techniquehttps://dergipark.org.tr/tr/pub/aucbd/issue/44490/551499hierarchical cluster analysispearson proksimity matrixturkeyprovincessocio-economic regions |
| spellingShingle | Murat KARABULUT Mehmet GÜRBÜZ Ersin Kaya SANDAL HİYERARŞİK KLUSTER (KÜME)TEKNİĞİ KULLANILARAK TÜRKİYE’DE İLLERİN SOSYO-EKONOMİK BENZERLİKLERİNİN ANALİZİ Coğrafi Bilimler Dergisi hierarchical cluster analysis pearson proksimity matrix turkey provinces socio-economic regions |
| title | HİYERARŞİK KLUSTER (KÜME)TEKNİĞİ KULLANILARAK TÜRKİYE’DE İLLERİN SOSYO-EKONOMİK BENZERLİKLERİNİN ANALİZİ |
| title_full | HİYERARŞİK KLUSTER (KÜME)TEKNİĞİ KULLANILARAK TÜRKİYE’DE İLLERİN SOSYO-EKONOMİK BENZERLİKLERİNİN ANALİZİ |
| title_fullStr | HİYERARŞİK KLUSTER (KÜME)TEKNİĞİ KULLANILARAK TÜRKİYE’DE İLLERİN SOSYO-EKONOMİK BENZERLİKLERİNİN ANALİZİ |
| title_full_unstemmed | HİYERARŞİK KLUSTER (KÜME)TEKNİĞİ KULLANILARAK TÜRKİYE’DE İLLERİN SOSYO-EKONOMİK BENZERLİKLERİNİN ANALİZİ |
| title_short | HİYERARŞİK KLUSTER (KÜME)TEKNİĞİ KULLANILARAK TÜRKİYE’DE İLLERİN SOSYO-EKONOMİK BENZERLİKLERİNİN ANALİZİ |
| title_sort | hiyerarsik kluster kume teknigi kullanilarak turkiye de illerin sosyo ekonomik benzerliklerinin analizi |
| topic | hierarchical cluster analysis pearson proksimity matrix turkey provinces socio-economic regions |
| url | https://dergipark.org.tr/tr/pub/aucbd/issue/44490/551499 |
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