Hi all.
I have sampled soil and vegetable in an area about 500 ha (24 samples from soil an vegetable). Also I have sampled from air in 12 station in this area. What I want to do in this research is: determining the impacts of air pollution on soil and vegetables in this area near an oil refinery.
I am trying to do statistical analysis to find the relation between air pollution and the concentration of TPHs and HMs in the soil and veg.
I know the regression and correlation are good but I do not know about multivariate analysis. What multivariate methods I can use in this research?
many thanks.
bests.
You may read and learn:
Gelman & Hill: Data Analysis Using Regression and Multilevel/Hierarchical Models, ISBN: 9780521686891
It describes the concept of (generalized) regression models, including multivariate models and also (as it might be relevant for your experimental setups) multilevel models.
Dear Javad
According to your objectives, I think multivariate regression Analysis is the best. Firstly, you should check correlation analysis between concentration of TPHs and HMs in the soil and veg with air pollution data and then find the degrees of the relationship with significant level. For multivariate regression analysis, consider the two regression model as 1) the air pollution data as independent and concentration of TPHs as dependent and 2) the air pollution data as independent and concentration of HMs as dependent variable and then you can estimate concentration level of TPHs and HMs due to air pollution. To perform this analysis, you can use like SPSS/ SAS/ R package or any statistical package. Please, find the attachment.
Best,
Test of significant variation maybe necessary since you have 12 stations.
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