As stated here: Do we use bootstrapping with population data?
"The general idea of bootstrap is that by sampling from your data you re-create the sampling process that happened when sampling your sample from the population."
So my question is:
Suppose I have a Population (P) and I take a big sample (called S), then I apply Bootstrap to that sample S to recreate my "sampling distribution". Once I have my estimator (let´s suppose the mean) of the bootstrap, my estimator would be close to the S sample estimator, ¿right? Assuming a big sample and big resamples.
But, does this boostrap estimator also corresponds to the "real" value of the population (P)? What happens if the first sample (S) I take from the population is biased?