Financial Risk Manager Part 1
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Assume that after constructing a multiple linear regression model, you find that R² = 0.97. How confident would you be in using the line of best fit for the purposes of prediction?
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TTanishq
A
Not confident.
B
Very confident.
C
The relationship would be too weak at predicting using a linear function.
D
The relationship would be random and hence impossible to predict.
Explanation:
Explanation
A high R² value of 0.97 indicates that 97% of the variability in the dependent variable can be explained by the independent variables in the model. This means that the model fits the data very well and the line of best fit accurately represents the data. Therefore, we can be very confident in using this model for prediction.
Key Points:
- R² Interpretation: The closer the R² value is to 1, the better the model fits the data
- 0.97 R²: This is considered very high, indicating a strong relationship between the independent and dependent variables
- Predictive Power: The model is likely to make accurate predictions due to the high explanatory power
Why Other Options Are Incorrect:
- Choice A: Incorrect because the high R² value indicates a strong relationship that should increase confidence in predictive use
- Choice C: Incorrect because an R² of 0.97 suggests a very strong linear relationship, not a weak one
- Choice D: Incorrect because a high R² value implies little randomness and that most data variation can be explained by the model
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