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,发现PM2.5与其它5个基本监测指标相关性显著。最后建立了武汉市城区PM2.5与其它5个基本监测指标的逐步回归模型,检验性预测证明模型是理想的。
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.
出处
《绿色科技》
2014年第6期149-152,共4页
Journal of Green Science and Technology
基金
华中农业大学国家级大学生创新创业训练计划(编号:201310504003)资助
关键词
武汉
PM2
5
独立性
相关性
逐步回归
Wuhan
PM2.5
independence
correlation
stepwise regression
