毕业论文移动版

摘要浙江省是全国经济发展大省，一直以来很受国家关注。本课题以2012统计年鉴数据为依据，选取25个相关统计指标，运用多元统计中的因子分析和聚类分析对其11个城市的经济进行实证分析和比较研究。根据统计学研究方法理论，把浙江省11个城市的综合经济实力作差异对比，并进行层次的划分。根据数据研究结果得出五个类别，然后分别对每类城市的经济发展水平进行综合评估，以此提出相关的经济政策和政治建议。经过因子分析和聚类分析结果表明：综合经济实力因子处于主导地位，生活质量因子位居其次，另外产业发展因子和农业发展因子在决定经济发展实力的高低方面也起到决定性作用。本课题认为利用因子分析和聚类分析相结合的方法研究市域经济，所得的结论客观、真实可信，能够较好地反应浙江省各市经济发展的实力水平和差异结构，也能客观的分析出各市经济发展的主要影响因素，为更好地发展浙江经济提出更有效的经济决策。46753

毕业论文关键词：浙江省；市域经济；因子分子；聚类分析

 Abstract Zhejiang status in the national economic development is important, historically much attention. In 2011 national economic and social development plans Bulletin basis, selected 25 relevant indicators, the use of factor analysis and cluster analysis of the level of economic development of Zhejiang Province, 11 cities were analyzed and compared empirical research. On this basis, the 11 cities in accordance with the strength of the overall economic strength are sorted and pided into five levels, on the level of urban economic development objective evaluation of different levels, and make relevant policy recommendations. The results show that: the overall level of response and quality of life, economic development level of comprehensive economic strength factor is dominant, while the role of the strength factor strength factor of agricultural development and industrial development is also highly valued. Thesis that the use of factor analysis and cluster analysis method of combining research city region economy, concluded objective, credible, can better reflect the level of economic development of cities in Zhejiang Province, but also an objective analysis of the impact of major cities for economic development factors for better economic development of Zhejiang propose effective economic decisions.

KeyWord：Areas Economy; Factor Molecules; Zhejiang Province, Cluster Analysis 

 目录

浙江省市域经济差异研究 1

1. 引言 5

2. 评价指标和评价方法 6

2.1评价指标及测算数据 6

3. 因子分析在市域经济研究中的应用 6

3.1因子分析模型及其步骤 6

3.2 样本数据及其来源 7

3.3 数据分析过程 8

3.3.1论文以SPSS作为数据处理和统计分析 8

3.3.2 将原始数据标准化后进行分析 8

4. 结果分析 10

4.1 因子分析结果 10

4.2 基于主因子得分的聚类分析 11

5. 结论及建议 15

参考文献 (责任编辑：qin)