I'm running a nonparametric bootstrap to estimate a confidence interval for the mean of a sample. My question is during this loop is it correct (or acceptable) to compute the skewness and kurtosis on the randomly sampled data for each iteration? This way I have a distribution of kurtosis and skewness (would plotting a histogram for these 2 be of useful information?).
However, if I still want a single estimate for the kurtosis and skewness, this would just be computed on the distribution of bootstrapped means?