I have a silly question on bootstrap methods for calculating p-value.
Suppose I have a dataset, which is likely normal distributed. Now I want to determine whether a particular value X is signifiant high in the dataset by giving a pvalue.
For me, there are two options
since the dataset is roughly normal distributed, I could calculate the sd and mean, get the area for z>(X-mean)/sd from Z table, and use it as pvalue.
by bootstrap. I could generate a new sample S (length N) from the original dataset by bootstrap, then get the p-value by sum(S>X)/ N.
My question is am I right to use bootstrap in 2nd option? Could you recommend books for better understanding bootstrap and permutation test?