I used an extract as a primer treatment on seedlings of wheat, and as results I have calculated several germination parameters. I also have the biochemical composition of the extract and now I would like to explore the possible correlations between the composition of the extracts and the obtained results. Is PCA a good choice or is there any other analysis that would be more optimal in my case?
PCA is primarily an exploratory method that is used to gain insight into complex datasets. You could use it to identify relevant parameters that contribute to variation within your response variables. Therefore, it can be a good initial choice while gaining better understanding of the data.
Not really. You would require ANOVA, PERMANOVA or a Generalised Additive Model :)
Dear Amer Chabili since you're assessing only one factor, it's not possible to run a PCA. In my opinion, and considering what are you looking for, a correlation test is the best choice.
To me correlation is the best as regards to what you are looking for.
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