 Lyapunov condition

For independent centered random variables with total variance $s_n^2$, the Lyapunov condition requires the displayed expression to tend to zero for some $\delta >0$. The inequality $z^2{1}_{\{|z|>\epsilon s_n\}}\le |z{|}^{2+\delta }/(\epsilon s_n{)}^{\delta }$ implies the Lindeberg condition after normalization. The Lindeberg-Feller central limit theorem then makes the normalized sum converge to the standard normal distribution.