Example Concept: Imputation methods like forward fill and backward fill are simple techniques where missing values are replaced with the last or next observed value, respectively. Interpolation techniques, such as linear interpolation, use surrounding data points to estimate missing values. Model-based approaches, like ARIMA or Kalman filters, can be used to predict missing values based on the underlying time series model, capturing trends and seasonality effectively.