Interpretation of coefficient of determination

If computing a causal linear regression model of y = a + bX and the resultant r2 is very near zero, then one would be able to conclude that:

1. y = a + bX is a good forecasting method.

2. Y = a + bX is not a good forecasting method.

3. a multiple linear regression model is a good forecasting method for the data.

4. a multiple linear regression model is not a good forecasting method for the data.

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Interpretation of coefficient of determination : If computing a causal linear regression model of y = a + bX and the resultant r2 is very near zero, then one would be able to conclude that: |

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