The owner of a construction firm objects to the model because it suggests that the number of bathrooms has no effect on the price of a home. He argues that, based on his experience, adding another bathroom increases the home's value. Do you agree with his comment about the model? Why or why not? (Include appropriate numerical support from the R output.) What could be explaining the output of this model when both Size and Baths are included as predictors of the selling price?

1 )] @ gradescope.com (] [ 4 (@ R AT S ] S ST ero (- RNt 25/34 Questions Answered 1 question with unsaved changes => Q3 Home prices 0 Points Many variables have an impact on determining the price of a house. Using a dataset containing a sample of homes for sale in Statesboro, Georgia. Here's the list of variables in the dataset: price: Selling price of the house (in thousands of dollars). size: Size of the house (in square feet). Baths : Number of bathrooms. Bedrooms : Number of bedrooms. Garage : Number of garage spaces. age : Age of the house (in years). The R output is provided below: Coefficients: Estimate Std. Error t value Pr(>|t]) (Intercept) -152037 85619 -1.78 0.110 Baths 9530 40826 0.23 0.821 Size 139467 46.67 300 0015 Multiple R-squared: 0.711, Adjusted R-squared: 0.646 Q3.1 skill Builder: Equation 0 Points Provide the regression equation for the model corresponding to the R output