摘要如今，气温的变化已经成为人类正面临的巨大课题，引起了人类的广泛关注。本文利用回归分析、主成分分析等方法研究了全国31个主要城市的年平均气温及可能的影响因素，包括水资源总量、臭氧日最大8小时第90百分位浓度、生活垃圾清运量、工业二氧化硫排放量、工业氮氧化物排放量、工业烟（粉）尘排放量、生活二氧化硫排放量、生活氮氧化物排放量、生活烟（粉）尘排放量、森林覆盖率、湿地面积占辖区面积比重、工业污染治理废气完成投资等因素.并根据软件运行结果分析找出气温变化和影响因素的关系.根据统计分析的结果,影响温度变化的主要因素是水资源总量、臭氧日最大8小时第90百分位浓度、生活垃圾清运量、工业二氧化硫排放量、工业氮氧化物排放量、工业烟（粉）尘排放量.因此，我们应该加大力度管理工业废气的排放，从日常生活中做好节能减排的工作.该论文有表7个，参考文献6篇.51799

毕业论文关键词：气温  回归分析  主成分分析  SPSS  

Analysis of The Influence Factors of The Temperature Change of Main Cities in China

Abstract Nowadays,temperature issue has become a big problem that we are faced with.The paper analyzes the statistics of average annual temperature of 31 cities in China and the  possible influence factors including gross amount of water resources, ozone daily maximum 8 hours ninetieth percentile concentration,gross amount of cleaning up of domestic garbage，industrial sulfur dioxide emissions,industrial nitrogen oxide emissions,industrial smoke and dust emissions,sulfur dioxide emissions from life,nitrogen oxide emissions from life,smoke and dust emissions from life，percent of forest cover,area of wetland area accounted for the proportion of area,industrial pollution control waste gas investment completed,and so on,which uses analysis of regression,principal component analysis (PCA).Founding out the relationships between temperature change and influence factors.The main influence factors to temperature changes are gross amount of water resources, ozone daily maximum 8 hours ninetieth percentile concentration,gross amount of cleaning up of domestic garbage，industrial sulfur dioxide emissions,industrial nitrogen oxide emissions,industrial smoke and dust emissions according to the results of statistical analysis.Therefore,we should step up efforts to the management of industrial waste gas emissions.

Key Words: Temperature  Analysis of Regression  Principal Components  SPSS  

 目  录

摘要----Ⅰ

Abstract----Ⅱ

目录----Ⅲ

表清单-Ⅳ

变量注释表Ⅳ

1 绪论--1

1.1气候变化问题----1

2 回归分析的理论与建模---1

2.1理论知识---- 2

2.2回归模型的建模过程3

2.3使用SPSS对年平均气温和可能的影响因素建立回归模型-- 3

3.主成分分析----6

3.1主成分分析理论-6

3.2使用SPSS对年平均气温和可能的影响因素主成分分析-- ---6

4.结论--- 8

5.参考文献-9 

致谢----10

表清单

表序号 表名称 页码

表2-1 相关性 6

表2-2 输入/移去的变量 7

表2-3 系数 8

表2-4 Anovab 9

表2-5 模型汇总 9

表3-1