Answer: $X_3$ should be included in the prediction equation since it was used in estimating the slope coefficients.

## Explanation The most accurate statement is that **$X_3$ should be included in the prediction equation since it was used in estimating the slope coefficients**. **Key Points:** 1. **Statistical significance vs. prediction accuracy**: Statistical significance relates to hypothesis testing about population parameters, while prediction focuses on minimizing forecast error. 2. **Omitting variables**: If $X_3$ is excluded from the prediction equation, it would change the estimated coefficients for $X_1$ and $X_2$ due to omitted variable bias, even if $X_3$ is not statistically significant. 3. **Estimation vs. prediction**: The coefficients $b_1$, $b_2$, and $b_3$ were estimated simultaneously in the model. Using the full model for prediction maintains the integrity of these coefficient estimates. 4. **Practical significance**: A variable may not be statistically significant but could still contribute to prediction accuracy, especially in out-of-sample forecasting. **Important**: While statistical insignificance might suggest removing $X_3$ for model simplification, for prediction purposes, the model should be used as estimated to avoid specification bias.

Author: LeetQuiz Editorial Team