The article explores how to estimate moments of statistics from large sets of data. By focusing on the distribution of data points, the researchers found conditions where these estimates are accurate, even with outliers. They used mathematical techniques like Taylor's series and functional differentiation to make these estimates. The study showed that these methods work well for estimating the variance of statistics from small to moderate data samples. Additionally, they improved on previous results by requiring fewer conditions for the moments of data points to converge to a normal distribution.