利用Matlab分析沈阳市住宅房产价格的影响因素  

The influence factors of residential real estate pices in Shenyang city by using Matlab analysis

作　　者：姜丽颖[1] 

机构地区：[1]沈阳城市建设学院基础部,辽宁沈阳110167

出　　处：《高师理科学刊》2015年第9期8-12,共5页Journal of Science of Teachers＇College and University

基　　金：2014年辽宁省普通高等教育本科教学改革研究项目(UPRP20140581)

摘　　要：结合近10年沈阳市相关经济数据,利用Matlab软件,通过散点图分析了GDP,人口数量,商品房住宅投资额,商品房住宅竣工面积,商品房住宅销售面积,城乡居民储蓄年末余额,社会商品零售总额,普通高等学校在校学生数和贷款利率等因素与住宅商品房平均销售价格的线性关系.并对这些基本要素进行多元线性回归,得到的回归方程系数,没能通过检验.再利用逐步回归分析的方法,通过两次筛选和剔除变量,得到了较理想的回归方程.由回归方程可以看出,GDP,人口数量,商品房住宅投资额,商品房住宅销售面积和城乡居民储蓄年末余额等对房产价格有显著的影响.这些分析结果对房产价格的预测和干预有一定的指导意义.According to the analysis of the related economic data of Shenyang city in recent l0 years, the Matlab software will be used to draw a scatter diagram for analyzing the GDP, population, commercial residential real estate investment, commercial residential real estate area, commercial housing sales area, closing balance of urban and rural residents＇ savings, total retail sales of social commodities, the number of students in colleges and universities, lending rates and other elements, which are related to the average selling price of residential real estate. And theses basic elements will do the multiple regression analysis to get the regression equation coefficient, which can not be passed the test. An ideal regression equation was obtained by using step wise regression analysis method, filtering and removing variables for two times. As it can be seen from the regression equation, the real estate prices can be remarkably affected by the GDP, population, residential real estate investment, commercial housing sales area and closing balance of urban and rural residents＇ savings. Thus these analysis results will have some implications on the prediction and intervention of real estate prices.

关 键 词：房产价格 影响因素 回归分析 

分 类 号：F293.3[经济管理—国民经济]