I have a dataset which displays the effect of a pollutant on the productivity of microorganisms and I am wanting to use a statistical test, to see if there are any statistical differences between the concentration of the pollutant and the productivity of the microbial community.
To investigate this, three different pollutant concentrations were trialed simultaneously over an 11 day period: a high pollutant concentration, a low pollutant concentration, and no pollutant. Each pollutant concentration had 4 replicates and productivity was measured every day over an 11 day period. The four replicates have been averaged and all data has been normalized.
Similar answers to this question e.g. this one, this one or this one are not exactly similar because the data in these examples differs to mine. I have data which is measured at equal intervals, I want to see if the pollutant effect is statistically significant in comparison to the no pollutant samples and I want this to be done for the entire time series, not just at a small number of time points.
From initial inspection, the ARIMA test seems to fit what I am looking for, I would, however, welcome any advice on using this test and any other options available.