A home appraisal company would like to develop a regression model that would predict the selling price of a house based on the age of the house in years (X1) , the living area of the house in square feet (X2) , and the number of bedrooms (X3) . The following regression model was chosen using a data set of house statistics:
$\hat { y }$ = 88,399.5547 + 91.3333x₂ + 31,471.1372x₃
The first house from the data set had the following values:
Selling price = $324,000 Age = 22 years
Square Feet = 2,000 Bedrooms = 3
The residual for this house is ______.

Question

A home appraisal company would like to develop a regression model that would predict the selling price of a house based on the age of the house in years (X1) , the living area of the house in square feet (X2) , and the number of bedrooms (X3) . The following regression model was chosen using a data set of house statistics:

\hat { y }

= 88,399.5547 + 91.3333x₂ + 31,471.1372x₃
The first house from the data set had the following values:
Selling price = $324,000 Age = 22 years
Square Feet = 2,000 Bedrooms = 3
The residual for this house is ______.

Quizplus · Accepted Answer

The Answer of A home appraisal company would like to develop a regression model that would predict the selling price of a house based on the age of the house in years (X1), the living area of the house in square feet (X2), and the number of bedrooms (X3). The following regression model was chosen using a data set of house statistics: $$\hat { y }$$ = 88,399.5547 + 91.3333x₂ + 31,471.1372x₃ The first house from the data set had the following values: Selling price = $324,000 Age = 22 years Square Feet = 2,000 Bedrooms = 3 The residual for this house is ______. A)- 41,480 B)10,216 C)- 16,095 D)23,558

A Home Appraisal Company Would Like to Develop a Regression y^\hat { y }y^​

A Home Appraisal Company Would Like to Develop a Regression $\hat { y }$