武汉城区PM2.5浓度的因素分析与其估算模型

吴克祥等

摘要：首先利用武汉市城区空气质量监测数据，通过运用SPSS软件对武汉市城区空气质量基本监测指标之间进行了独立性检验，发现各指标变量之间的不具独立性，即各变量之间具有一定关系。然后对各监测指标之间的相关性进行了分析，利用SPSS软件求得各指标之间的相关系数，判断各变量之间相关性是否显著，

关键词：武汉；PM2.5；独立性；相关性；逐步回归

中图分类号：X823

文献标识码：A 文章编号：16749944（2014）06014904

1 引言

参考文献：

Factor Analysis of PM2.5 Concentration in Wuhan Urban Area and its Estimation Model

Wu Kexiang， Yang Chongrui， Jiang Yue， Zhang Wenbo， Kuang Faguo

（College of Resources and Environment， Huazhong Agricultural University， Wuhan 430070， China

）

Abstract： On the basis of air quality monitoring data of Wuhan urban areas， this article uses SPSS to conduct an independence test among basic indexes of air quality. The resulst show that different index variables are not independent， which means they are related to each other. And then it carries out a correlation analysis among these indexes again， and uses SPSS to calculate their correlation coefficients in order to find out whether the correlation between variables is significant. The results indicate that PM2.5 has significant correlations with five other basic monitoring indexes. At last， the article builds a stepwise regression model of PM2.5 and other five basic monitoring indexes， which inspection prediction proves that the model is ideal.

Key words： Wuhan； PM2.5； independence； correlation； stepwise regressionendprint

摘要：首先利用武汉市城区空气质量监测数据，通过运用SPSS软件对武汉市城区空气质量基本监测指标之间进行了独立性检验，发现各指标变量之间的不具独立性，即各变量之间具有一定关系。然后对各监测指标之间的相关性进行了分析，利用SPSS软件求得各指标之间的相关系数，判断各变量之间相关性是否显著，

关键词：武汉；PM2.5；独立性；相关性；逐步回归

中图分类号：X823

文献标识码：A 文章编号：16749944（2014）06014904

1 引言

参考文献：

Factor Analysis of PM2.5 Concentration in Wuhan Urban Area and its Estimation Model

Wu Kexiang， Yang Chongrui， Jiang Yue， Zhang Wenbo， Kuang Faguo

（College of Resources and Environment， Huazhong Agricultural University， Wuhan 430070， China

）

Abstract： On the basis of air quality monitoring data of Wuhan urban areas， this article uses SPSS to conduct an independence test among basic indexes of air quality. The resulst show that different index variables are not independent， which means they are related to each other. And then it carries out a correlation analysis among these indexes again， and uses SPSS to calculate their correlation coefficients in order to find out whether the correlation between variables is significant. The results indicate that PM2.5 has significant correlations with five other basic monitoring indexes. At last， the article builds a stepwise regression model of PM2.5 and other five basic monitoring indexes， which inspection prediction proves that the model is ideal.

Key words： Wuhan； PM2.5； independence； correlation； stepwise regressionendprint

摘要：首先利用武汉市城区空气质量监测数据，通过运用SPSS软件对武汉市城区空气质量基本监测指标之间进行了独立性检验，发现各指标变量之间的不具独立性，即各变量之间具有一定关系。然后对各监测指标之间的相关性进行了分析，利用SPSS软件求得各指标之间的相关系数，判断各变量之间相关性是否显著，

关键词：武汉；PM2.5；独立性；相关性；逐步回归

中图分类号：X823

文献标识码：A 文章编号：16749944（2014）06014904

1 引言

参考文献：

Factor Analysis of PM2.5 Concentration in Wuhan Urban Area and its Estimation Model

Wu Kexiang， Yang Chongrui， Jiang Yue， Zhang Wenbo， Kuang Faguo

（College of Resources and Environment， Huazhong Agricultural University， Wuhan 430070， China

）

Abstract： On the basis of air quality monitoring data of Wuhan urban areas， this article uses SPSS to conduct an independence test among basic indexes of air quality. The resulst show that different index variables are not independent， which means they are related to each other. And then it carries out a correlation analysis among these indexes again， and uses SPSS to calculate their correlation coefficients in order to find out whether the correlation between variables is significant. The results indicate that PM2.5 has significant correlations with five other basic monitoring indexes. At last， the article builds a stepwise regression model of PM2.5 and other five basic monitoring indexes， which inspection prediction proves that the model is ideal.

Key words： Wuhan； PM2.5； independence； correlation； stepwise regressionendprint