Question $12(2$ points$)$

A developer who specializes in summer cottage properties is considering purchasing a large tract of land adjoining a lake. The current owner of the tract has already subdivided the land into separate building lots and has prepared the lots by removing some of the trees. The developer wants to forecast the value of each lot. From previous experience, she knows that the most important factors affecting the price of a lot are size, number of mature trees, and distance to the lake. From a nearby area, she gathers the relevant data for $60$ recently sold lots.

The following summary output shows the result of a multiple regression analysis that helps to determine weekly gross sales based on the other variables.

What does the adjusted R$-$squared value tell you about the model?

Question $12$ options:

Approximately $40\mathrm{.}24\%$ of the variability in the dependent variable is not accounted for by the model.

The adjusted R$-$squared value indicates that the independent variables have no significant relationship with the dependent variable.

Approximately $20\mathrm{.}1\%$ of the variability in the dependent variable can be explained by the model.

The model has very high predictive accuracy since it explains more than $40\%$ of the variance in the dependent variable.