Question

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 |
||

5.0 |

Answer #1

**Answer:**

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

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