If two linear regression models have the same number of explanatory variables, a model with an r2 value of 0.45 is a better prediction model than a model with an r2 value of 0.65.
true
false

False

Step-by-step explanation:

Given that two linear  regression models have the same number of explanatory variables

First model has coefficient of determination as 0.45 while other

0.65

we know that R^2 is the proportion showing the variation of dependent because of variation in independent variables.

Hence a higher R square is always better because it ensures more linearity and hence more accuracy in the regression equation.

Hence 0.65 model is better than 0.45 model.

The given statement is false.

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step-by-step explanation: