For the Same Set of Observations on a Specified Dependent $$\begin{array}{l} \text { Model 1 } \quad \text { Model 2 } \\{ r ^ { 2 } = .92 }\quad { r ^ { 2 } = .85 }\\s = 1.65 \quad s = 1.91\end{array}$$

Multiple Choice

For the same set of observations on a specified dependent variable,two different independent variables were used to develop two separate simple linear regression models.A portion of the results is presented below. $$\begin{array}{l} \text { Model 1 } \quad \text { Model 2 } \\{ r ^ { 2 } = .92 }\quad { r ^ { 2 } = .85 }\\s = 1.65 \quad s = 1.91\end{array}$$



Based on the results given above,we can conclude that:

A) A prediction based on Model 1 is better than a prediction based on Model 2.
B) A prediction based on Model 2 is better than a prediction based on Model 1.
C) There is no difference in the predictive ability between Model 1 and Model 2.
D) There is not sufficient information to determine which of the two models is superior for prediction purposes.