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摘要中国经济飞速发展，城镇化进程不断加快，城市用地需求不断增加，土地的价格也跟着上涨。老百姓进城购房，住宅的需求量增加，这导致房价上涨，住宅用地价格也跟着上涨。因此，有必要对住宅用地的价格的影响因素进行研究，探索住宅用地价格影响因素的相关程度。本文以徐州为例，对住宅用地价格的相关影响因素进行分析，再结合统计资料数据，运用spss软件进行相关分析，希望能够直观的反应出各个相关因素与住宅用地价格之间的关系，并找出他们之间的相关程度。为政府在制定出让土地价格的时候，提高参考依据；也为开发商在购买土地时，提供一定的借鉴。39157
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本文主要研究影响住宅用地价格的微观因素,在宏观因素一定的情况下,微观因素对住宅用地价格的高低起决定性作用。运用spss软件对采集到的6个相关因素进行处理，结果发现建筑密度与住宅用地价格的相关性可信度不达标，其他影响因素的可信度都达标，四个正相关因子和一个负相关因子；其中，与与住房用地价格相关性最大的是公交站数高达98.2%，最小的是容积率只有61.3%；他们与住宅用地价格相关性排序如下：公交站数>道路数>绿化率>离中心距离>容积率。
毕业论文关键词：相关分析，土地价格影响因素，住房用地
Abstract China's rapid economic development, the process of urbanization continues to accelerate, urban land demand continues to increase, the price of land also follow up. People into the city house, the increase in demand for residential, which led to rising prices, residential land prices also follow up. Therefore, it is necessary to study the factors that affect the price of residential land, and explore the correlation degree of the factors of residential land price.. The in Xuzhou, for example, for residential use price related factors were analyzed, combined with statistical data, using SPSS software analysis, hope to be able to direct response from all relevant factors and residential relationship between price, and find out the correlation between them. For the government in the formulation of land prices, improve the reference basis; also for developers in the purchase of land, to provide a certain reference.
This paper mainly studies the micro factors that affect the price of residential land, in the macro factor, the micro factor plays a decisive role in the price of residential land.. Using SPSS software to process the collected six related factors. The results showed that building density and residential use price correlation credibility is not up to the standard, the credibility of the other factors are standard, four positive correlation factor and a negative correlation factor; among them, and with the housing with the price correlation largest is bus stop number up to 98.2%, the minimum is only 61.3% volume rate; they and residential use price relevance sorting is as follows: bus station number > road number> greening rate>covered distance from the center>volume ratio.
Key words: correlation analysis land price influencing factors residential land
目 录
摘 要 II
Abstract III
1 绪论 VI
1.1 研究背景 VI
1.2 研究意义 VI
1.3 文献综述 VII
1.3.1 国内相关文献综述 VII
1.3.2 国外相关文献综述 VIII
1.4 研究内容及方法 VIII
1.4.1 研究方法及思路 VIII
1.4.2 研究内容 VIII
1.5 研究目的 VIII
2 住宅用地价格的影响因素定性分析 IX
2.1 城市规划对土地价格的影响 IX