Second-order statistics are statistical measures that provide information about the variability and correlation structure of a dataset, often used to analyze the relationships between variables. They include metrics such as variance, covariance, and correlation, which are fundamental in fields like signal processing, finance, and machine learning for understanding data behavior beyond central tendency.