高校欠费情况的空间统计分析  

Spatial Autocorrelation Analysis of University Students into Arrears

作　　者：孟庆书[1] 罗粤舟[1] 彭湛霞[1] 

机构地区：[1]华南农业大学,广东广州510642

出　　处：《广东交通职业技术学院学报》2010年第2期79-82,共4页Journal of Guangdong Communication Polytechnic

摘　　要：文中采用空间自相关方法,采用邻接原则构造空间邻接矩阵,选用全局Moran'S I指数和局部Moran'SI指数对广东省某高校的广东各地区生源的学生欠费人数和学生欠费比例进行了详细的研究。全局Moran'SI指数表明该高校广东省各地区的学生欠费人数与学生欠费比例都存在着空间正相关,但是学生欠费比例的空间自相关程度更强。局部Moran'S I指数表明该高校学生欠费情况较严重的地区存在着空间的聚集,形成了两个聚集点:一个是以湛江、茂名、阳江、云浮、肇庆为主的广东省西部;一个是以河源、汕尾、梅州为主的广东省东北部地区。Spatial Autocorrelation Analysis is used to measure the number and the proportion of university students into arrears.All these students are from different districts in Guangdong province and are studying at the same university. Contiguity Based Spatial Weights,Global Moran＇s I and Local Moran＇s I are computed.The Global Moran＇s I identified that positive spatial autocorrelation is presented in terms of the number and the proportion of university students into arrears,and spatial aggregation degree of the proportion of the students is also higher than that of the number. The Local Moran＇s I identified two high cluster regions presented：One is the western part of Guangdong province including Zhanjiang,Maoming,Yangjiang,Yunfu and Zhaoqing.The other is the northeastern part of Guangdong province involving Heyuan,Shanwei and Meizhou.

关 键 词：空间统计学 全局空间自相关 局部空间自相关 空间邻接矩阵 

分 类 号：G475[文化科学—教育学]