Recently while passing one course (on datacamp) I got acquainted with two methods of resampling ( I used them to simulate statistical hypothesis) :
1.Bootstrap resampling when we choose samples with replacement of the size n from the main sample of the size n. We repeat this operation several times.
2.Permutation resampling when we scramble two arrays and relabel them. We also repeat this operation several times.
I am quite new in statistics and I have question: When it's better to choose th bootstrap and when permutation resampling?Are there any restrictions? Maybe there are any literature devoted to this?
Thanks for response!
Tim