Which practice is recommended to improve understanding of forecast results?

Which practice is recommended to improve understanding of forecast results?

• A. Focus only on numerical error metrics
• B. Avoid plotting data and residuals
• C. Visual exploration of data helps reveal issues not obvious in tables
• D. Rely solely on the latest observation for predictions

Answer: (C)

Visual exploration of data helps reveal issues not obvious in tables. Numbers like RMSE or MAE summarize overall accuracy, but they don’t show where and why forecasts go wrong. By plotting actual versus forecast values over time and examining residuals against fitted values, you can spot patterns such as systematic bias, trends in errors, seasonality in residuals, or changing variance. These visual cues point to model misspecification, missing factors, or the need for transformations and different modeling choices. This approach provides diagnostic insight that raw metrics miss, guiding improvements beyond what a single numeric score can suggest. The other options miss or conceal these diagnostic signals: focusing only on metrics ignores patterns; avoiding plots eliminates the chance to see residual structure; and relying only on the latest observation ignores the historical context that informs reliable forecasting.

Visual exploration of data helps reveal issues not obvious in tables. Numbers like RMSE or MAE summarize overall accuracy, but they don’t show where and why forecasts go wrong. By plotting actual versus forecast values over time and examining residuals against fitted values, you can spot patterns such as systematic bias, trends in errors, seasonality in residuals, or changing variance. These visual cues point to model misspecification, missing factors, or the need for transformations and different modeling choices. This approach provides diagnostic insight that raw metrics miss, guiding improvements beyond what a single numeric score can suggest. The other options miss or conceal these diagnostic signals: focusing only on metrics ignores patterns; avoiding plots eliminates the chance to see residual structure; and relying only on the latest observation ignores the historical context that informs reliable forecasting.