Question

# Ford would like to develop a regression model that would predict the number of cars sold...

Ford would like to develop a regression model that would predict the number of cars sold per month by a dealership employee based on the employee's number of years of sales experience (X1), the employee's weekly base salary before commissions (X2), and the education level of the employee. There are three levels of education in the sales force—high school degree, associate's degree, and bachelor's degree. The following dummy variables have been defined.

 Degree X3 X4 High School 0 0 Associate's 0 1 Bachelor's 1 0

The following regression model was chosen using a data set of employee statistics:

= 2.6267 + 0.0135x2 + 3.3404x3 + 2.4237x4

The first employee from the data set had the following values:

Sales = 11

Experience = 3 years

Salary = \$498

Education = Bachelor's degree

The residual for this employee is ________.

 -3.6 -1.7 0.9 5

Given Data

Given regression model is ,

The first employee from the data set had the following values:

Sales = Y = 11

Experience = = 3 years

Salary = = \$498

Education = Bachelor's degree

&

= 11 - 12.6901

= - 1.6901

The residual for this employee is -1.6901

The residual for this employee is -1.7

It is very important to me.

Thank you for supporting me..