The simplest version of the central limit theorem (CLT) says that if \(X_1, \dots, X_n\) are iid random variables with mean \(\mu\) and finite variance \(\sigma^2\)
\[ \frac{\bar{X}_n - \mu}{\sigma/\sqrt{n}} \rightarrow_d N(0,1) \] where \(\bar{X}_n = \frac{1}{n} \sum_{i=1}^n X_i\).