Robust statistics is a field within statistical methodology focused on developing and analyzing procedures that are less sensitive to departures from idealized assumptions, such as model misspecification or the presence of outliers, than classical statistical methods. It investigates methods designed to provide valid and efficient inferences even under small deviations from theoretical conditions, thereby enhancing the reliability and trustworthiness of statistical conclusions in practical applications where data may not perfectly conform to theoretical models.