Answer-first summary for fast verification
Answer: Model 3
## Explanation For **prediction purposes**, we should primarily focus on **Akaike's Information Criterion (AIC)** as it's specifically designed for model selection when the goal is prediction. **Analysis of criteria:** - **AIC**: Lower values indicate better models for prediction - Model 1: 13.156 - Model 2: 14.287 - Model 3: 12.463 **(lowest - best for prediction)** - **Adjusted R²**: Higher values are better, but Model 2 (0.652) is slightly better than Model 3 (0.648) - **BIC**: Lower values are better, but BIC penalizes complexity more heavily and is better for finding the "true" model rather than prediction **Decision rationale:** - AIC is the preferred criterion for prediction - Model 3 has the lowest AIC (12.463) despite having slightly lower adjusted R² than Model 2 - The small decrease in adjusted R² from Model 2 to Model 3 is outweighed by the significant improvement in AIC Therefore, **Model 3** should be preferred for prediction purposes.
Author: LeetQuiz Editorial Team
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An analyst gathers the following summary of the goodness-of-fit measures for a dependent variable regressed on alternative sets of factors:
| Independent Variables | Adjusted | Akaike's Information Criterion (AIC) | Schwarz's Bayesian Information Criterion (BIC) |
|---|---|---|---|
| Model 1: Factor 1 | 0.631 | 13.156 | 14.990 |
| Model 2: Factors 1 and 2 | 0.652 | 14.287 | 15.189 |
| Model 3: Factors 1, 2, and 3 | 0.648 | 12.463 | 16.397 |
Which of the models should be preferred for prediction purposes?
A
Model 1
B
Model 2
C
Model 3