Let's say I have a model that gives me projected values. I calculate RMSE of those values. And then the standard deviation of the actual values.
Does it make any sense to compare those two values (variances)? What I think is, if RMSE and standard deviation is similar/same then my model's error/variance is the same as what is actually going on. But if it doesn't even make sense to compare those values then this conclusion could be wrong. If my thought is true, then does that mean the model is as good as it can be because it can't attribute what's causing the variance? I think that last part is probably wrong or at least needs more information to answer.