吳克祥等

摘要：首先利用武漢市城區(qū)空氣質(zhì)量監(jiān)測數(shù)據(jù)，通過運用SPSS軟件對武漢市城區(qū)空氣質(zhì)量基本監(jiān)測指標(biāo)之間進(jìn)行了獨立性檢驗，發(fā)現(xiàn)各指標(biāo)變量之間的不具獨立性，即各變量之間具有一定關(guān)系。然后對各監(jiān)測指標(biāo)之間的相關(guān)性進(jìn)行了分析，利用SPSS軟件求得各指標(biāo)之間的相關(guān)系數(shù)，判斷各變量之間相關(guān)性是否顯著，

關(guān)鍵詞：武漢；PM2.5；獨立性；相關(guān)性；逐步回歸

中圖分類號：X823

文獻(xiàn)標(biāo)識碼：A 文章編號：16749944（2014）06014904

1 引言

參考文獻(xiàn)：

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：首先利用武漢市城區(qū)空氣質(zhì)量監(jiān)測數(shù)據(jù)，通過運用SPSS軟件對武漢市城區(qū)空氣質(zhì)量基本監(jiān)測指標(biāo)之間進(jìn)行了獨立性檢驗，發(fā)現(xiàn)各指標(biāo)變量之間的不具獨立性，即各變量之間具有一定關(guān)系。然后對各監(jiān)測指標(biāo)之間的相關(guān)性進(jìn)行了分析，利用SPSS軟件求得各指標(biāo)之間的相關(guān)系數(shù)，判斷各變量之間相關(guān)性是否顯著，

關(guān)鍵詞：武漢；PM2.5；獨立性；相關(guān)性；逐步回歸

中圖分類號：X823

文獻(xiàn)標(biāo)識碼：A 文章編號：16749944（2014）06014904

1 引言

參考文獻(xiàn)：

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：首先利用武漢市城區(qū)空氣質(zhì)量監(jiān)測數(shù)據(jù)，通過運用SPSS軟件對武漢市城區(qū)空氣質(zhì)量基本監(jiān)測指標(biāo)之間進(jìn)行了獨立性檢驗，發(fā)現(xiàn)各指標(biāo)變量之間的不具獨立性，即各變量之間具有一定關(guān)系。然后對各監(jiān)測指標(biāo)之間的相關(guān)性進(jìn)行了分析，利用SPSS軟件求得各指標(biāo)之間的相關(guān)系數(shù)，判斷各變量之間相關(guān)性是否顯著，

關(guān)鍵詞：武漢；PM2.5；獨立性；相關(guān)性；逐步回歸

中圖分類號：X823

文獻(xiàn)標(biāo)識碼：A 文章編號：16749944（2014）06014904

1 引言

參考文獻(xiàn)：

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