University of Isfahan Geography and Environmental Planning 2008-5362 28 2 2017 08 23 Spatial Distribution of Quality of Life and Identification of its Determinants in Rural Settlements (Case Study: Ravansar County in Kermanshah Province) Spatial Distribution of Quality of Life and Identification of its Determinants in Rural Settlements (Case Study: Ravansar County in Kermanshah Province) 57 78 22255 10.22108/gep.2017.97940 FA Davood Jamini PhD in Geography and Rural Planning, Young Researchers and Elite Club, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran Masuod Safari Aliakbari Assistant Professor of Geography and Rural Planning, Faculty member of Payame Noor University, Tehran, Iran Maryam Salahi Kakhaki PhD Student of entrepreneurship planning in rural areas in Islamic Azad University of Mashhad, Mashhad, Iran Khaled Alipoor Young Researchers and Elite Club, Sardasht Branch, Islamic Azad University, Sardasht, Iran Amirai Zolfaghari PhD student Geography and Rural Planning University of Isfahan, Isfahan, Iran Journal Article 2014 12 25 The research method was descriptive-survey and its purpose was to assess the quality of life in rural of Ravansar Township. The population of this research is total household tutelars of 95 villages which their population was above 20 households. So, 379 questionnaires, which their validity and reliability was confirmed by scientific approaches, were distributed among 95 of rural settlements. To analyze data and display rural settlements quality of life, SPSS and GIS softwares were used, respectively. The results showed that situation of quality of life, with a mean of 2.14 and standard deviation of 0.84 is an unsuitable situation among rural settlements. Calculations of variance analysis suggested that there is a significant difference among 95 of sample settlements in terms of quality of life. The results of the analyses using Cluster Analysis regarding the present inequality among rural settlements showed that 6 percent of total settlements (with a mean of 3.48 of quality of life) are located in the first cluster, 15 percent of total settlements (with a mean of 2.63 of quality of life) in the second cluster and 79 percent of total settlements (with a mean of 1.95 of quality of life) in the third cluster, respectively. Spatial display of quality of life indicated that there is a low quality of life in the studied area. The results of identification of quality of life determinants, using Multi Variable Regression, also showed that 7 of independent variables calculated around 75.6 percent of total dependent variance. These independent variables are: status of economic-social, ownership of capital oriented resources, household dimension, access to services and facilities, access to credits, supportive policies and management factors. The research method was descriptive-survey and its purpose was to assess the quality of life in rural of Ravansar Township. The population of this research is total household tutelars of 95 villages which their population was above 20 households. So, 379 questionnaires, which their validity and reliability was confirmed by scientific approaches, were distributed among 95 of rural settlements. To analyze data and display rural settlements quality of life, SPSS and GIS softwares were used, respectively. The results showed that situation of quality of life, with a mean of 2.14 and standard deviation of 0.84 is an unsuitable situation among rural settlements. Calculations of variance analysis suggested that there is a significant difference among 95 of sample settlements in terms of quality of life. The results of the analyses using Cluster Analysis regarding the present inequality among rural settlements showed that 6 percent of total settlements (with a mean of 3.48 of quality of life) are located in the first cluster, 15 percent of total settlements (with a mean of 2.63 of quality of life) in the second cluster and 79 percent of total settlements (with a mean of 1.95 of quality of life) in the third cluster, respectively. Spatial display of quality of life indicated that there is a low quality of life in the studied area. The results of identification of quality of life determinants, using Multi Variable Regression, also showed that 7 of independent variables calculated around 75.6 percent of total dependent variance. These independent variables are: status of economic-social, ownership of capital oriented resources, household dimension, access to services and facilities, access to credits, supportive policies and management factors. https://gep.ui.ac.ir/article_22255_a32a17c4e834e6ad9607299b18cf6fc8.pdf