Interpretation of "low variance" in PCA I have a question to ask about the interpretation of the PCA result.
The context concerns biological samples (spectroscopically analyzed) divided into treated and untreated samples (control)
If the first principal components describe only a small part of the variance (eg 15-16%) it means that they are not able to represent the entire variance of the system. If no main component can explain a good part of the variance of the system, can it be said that no predictor has a strong influence on the system and that therefore no strong differences are observed between a treated and untreated?
I honestly believe I cannot draw this conclusion.
I think that "low variance" explained means that the items are not sufficient to explain the model.
Thank you!

If the variance is "low" in every PC then you can conclude that no linear combination of variables can explain much variability, and this does include individual variables also since if you set all loadings to 0 except for 1 variable then this is equal to using only that variable.
