Example Concept: In time series analysis, missing data can be addressed using methods such as forward filling, backward filling, or interpolation. Forward filling involves replacing missing values with the last observed value, while backward filling uses the next observed value. Interpolation estimates missing values based on the surrounding data points, often using linear or spline methods. The choice of method depends on the data's characteristics and the analysis goals.