Statistical robustness refers to the ability of a statistical method to provide accurate and reliable results even when the assumptions of the method are violated or when there are outliers in the data. Robust statistical techniques are essential in real-world data analysis because they enhance the validity and reliability of the conclusions drawn from potentially noisy or imperfect data.