Can you suggest me some good data analysis techniques to use? I've a dataset in which I need to determine whether noise (traffic) makes the air more polluted or not. I have a dataset which contains info about noise, pm10, pm25 etc. What techniques should I use in order to clarify whether my hypothesis of Noise (traffic) makes air more polluted is true or not? I have found some but I'm not so sure if they're the right one or not. The ones I currently have are conjoint analysis machine learning, discriminant analysis, canonical correlation analysis, structural equation modeling, multidimensional scaling and cohort analysis. Are these good? Should I include some other techniques?

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Thanks in advance