You need to develop a model to predict the selling price of houses in a small city, based on assessed value, time in months since the house was reassessed, and whether the house is new

no and $1=$ yes$).$ A sample of $30$ recently sold single$-$family houses that were reassessed at full value one year prior to the study is selected and the results are in the given table. Develop

the most appropriate multiple regression model to predict selling price.

Click here to view the data.

Let $x_1$ represent assessed value, let $x_2$ represent time since the house was reassessed, and let $x_3$ represent whether the house is new. Which models are good according to the best$-$subsets

regression? Select all that apply.

A$.x_1$

B$.x_1{x}_2$

C$.x_2$

D$.x_1{x}_3$

E$.x_3$

F$.x_2{x}_3$

$\text{'}$G$.x_1{x}_2{x}_3$

H$.$ No models meet the requirements.

Based on a full analysis of the best model, which terms should be added? Select all that apply.

A$.$ An interaction term $x_1{x}_2$

B$.$ A quadratic term $x_1^2$

C$.$ An interaction term $x_1{x}_3$

D$.$ A quadratic term $x_2^2$

E$.$ An interaction term $x_2{x}_3$

F$.$ A quadratic term $x_3^2$

G$.$ No terms need to be added.

What is the final model?

$($Round to four decimal places as needed.$)$