EXAMINING SPATIAL VARIABILITY IN THE ASSOCIATION BETWEEN SOME FACTORS AND NUMBER OF PRISONERS IN TURKEY: A GWR ANALYSIS

Year 2021, , 141 - 148, 29.06.2021

Bahadır Yüzbaşı , Çetin Görür

https://doi.org/10.22531/muglajsci.928734

Cited By: 1

Abstract

The crime phenomenon requires an economic as well as a sociological analysis in terms of its occurrence, its causes and its consequences. In this study, the effects of socio-economic factors on crime were investigated by using Multiple Linear Regression and Geographical Weighted Regression Methods. The aim of the study is to analyze the factors that have an effect on crime, as well as to analyze which of the regression methods used gives more effective results. Method comparisons were made using R square and Akaike's Information Criterion. As a result of the analysis, it was seen that the Geographic Weighted Regression gave more effective results than the Multiple Linear Regression. In the study, Turkey's 81 provinces were included in the analysis and used the data of the year 2019. The number of prisoners is dependent variable, migration, literacy rate and unemployment rate are independent variables. The data used in this study are taken from the official web address Turkey Statistical Institute. Analyzes were made using the statistical R program.

Keywords

Geographic Weighted Regression, Multiple Linear Regression, Akaike

TÜRKİYE'DEKİ BAZI FAKTÖRLER İLE MAHKUM SAYISI ARASINDAKİ İLİŞKİDE MEKANSAL DEĞİŞKENLİĞİN İNCELENMESİ: BİR GWR ANALİZİ

Abstract

Suç olgusu, hem ortaya çıkış biçimi ve nedenleri ve hem de sonuçları açısından sosyolojik olduğu kadar ekonomik bir çözümlemeyi de gerekli kılmaktadır. Bu çalışmada, sosyo-ekonomik faktörlerin suç üzerindeki etkileri Çoklu Doğrusal Regresyon ve Coğrafik Ağırlıklı Regresyon Yöntemleri kullanılarak araştırılmıştır. Çalışmanın amacı, suç üzerinde etkili olan faktörleri analiz etmenin yanı sıra kullanılan regresyon yöntemlerinden hangisinin daha etkili sonuçlar verdiğini analiz etmektir. Yöntem karşılaştırmaları R^2 ve Akaike Bilgi Kriteri kullanılarak yapılmıştır. Analiz sonucu olarak Coğrafik Ağırlıklı Regresyonun Çoklu Doğrusal Regresyondan daha etkili sonuçlar verdiği görülmüştür. Çalışmada, Türkiye'nin 81 ili analize dahil edilmiş ve 2019 yılına ait veriler kullanılmıştır. Mahkûm sayısı bağımlı değişken, göç, okuryazar oranı ve işsizlik oranı bağımsız değişkenlerdir. Çalışmada kullanılan veriler Türkiye İstatistik Kurumu resmi web adresinden alınmıştır. Analizler istatiksel R programı kullanılarak yapılmıştır.

Keywords

Coğrafik Ağırlıklı Regresyon, Çoklu Doğrusal Regresyon, Akaike Bilgi Kriteri

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