案例,spss,数据分析

城市综合发展实力评价--以江苏省为例


全文字数:9000字左右  原创时间:<=2022年

【内容摘要】

城市综合发展实力评价--以江苏省为例


江苏省是中国综合发展水平最高的省份。人均GDP、综合竞争力、区域发展和民生指数均居全国各省首位。研究江苏省经济发展的差异性具有重要意义。
本文搜集了江苏省十三个地级市的十个国民经济指标数据,使用SPSS statistics中的因子分析与聚类分析,对十三个地级市进行经济发展水平排名,定义因子个数为2时排名与实际结果不符。重新定义因子个数后,得到改良后的城市排名,苏州的城市综合发展水平得分最高,其次是南京,排名第三的城市是无锡,三者都是独一档的水平。排名第四类的城市有常州和南通,南通的发展水平要略好于常州。排在第五类的城市有徐州、盐城、扬州、镇江和泰州。其中徐州属于第五类中发展最好的城市,盐城、扬州、镇江和泰州属于发展程度极其接近的城市。连云港、淮安、宿迁这三座城市在我们的排名中处于最后,但淮安和连云港的情况要略好于宿迁。
最后,我们针对整体城市的发展提出了相关的措施建议。

关键词:因子分析;聚类分析;SPSS;城市发展水平 
Abstract
Jiangsu ranks first among all provinces in China in terms of per capita GDP, comprehensive competitiveness, regional development and livelihood index, and is the province with the highest level of comprehensive development in China. It is very important to study the differentiation of economic development of different prefecture-level cities in jiangsu province for domestic economic development forecast.
This paper collects ten national economic index data of 13 prefecture-level cities in jiangsu province, and USES factor analysis and clustering analysis in SPSS statistics to rank the economic development level of 13 prefecture-level cities. When the number of factors is 2, the ranking is inconsistent with the actual results. After redefining the number of factors, the improved city ranking was obtained. Suzhou scored the highest in the comprehensive development level of the city, followed by nanjing, and wuxi ranked the third, all of which were the only level. In the fourth category, there are changzhou and nantong, and the development level of nantong is slightly better than that of changzhou. In the fifth category are xuzhou, yancheng, yangzhou, zhenjiang and taizhou. Xuzhou is the best developed city in the fifth category, while yancheng, yangzhou, zhenjiang and taizhou are very similar. Lianyungang, huai 'an and suqian are the last cities in our ranking, but huai 'an and lianyungang are slightly better than suqian.
Finally, we put forward relevant measures and suggestions for the development of the whole city.

Key words: Factor analysis; Cluster analysis; SPSS; Urban development level

 

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