Using a sample standard deviation to estimate the standard error is computationally easier than using bootstrapping. 
However, to correct for the approximation, you need to use a t-distribution when transforming the test statistic to 
get the p-value.

When the standard error is estimated from the sample standard deviation and sample size, the test statistic is transformed 
into a p-value using the t-distribution.