Question

An investigator developed a multiple regression model for employee salaries at a particular company. In this multiple regression model, the salaries are in thousands of dollars. For example, a data entry of 35 for the dependent variable indicates a salary of $35,000. The indicator variable for gender is coded as if male and if female. The computer output of this multiple regression model shows that the coefficient for this variable is -4.2. The t test showed that was significant at the 0.05 level. This result implies that for male and female workers of the company,

Choices below on the average, salaries do not differ. |

on the average, males earn $4,200 less. |

on the average, females have 4.2 more years of experience. |

on the average, females earn $4,200 less. |

on the average, males have 4.2 more years of experience. |

Answer #1

**Solution:**

An investigator developed a multiple regression model for employee salaries at a particular company. In this multiple regression model, the salaries are in thousands of dollars. For example, a data entry of 35 for the dependent variable indicates a salary of $35,000. The indicator variable for gender is coded as if male and if female. The computer output of this multiple regression model shows that the coefficient for this variable is -4.2. The t test showed that was significant at the 0.05 level. This result implies that for male and female workers of the company,

**c) on the
average, females earn $4,200 less.**

The following multiple regression printout can be used to
predict a person's height (in inches) given his or her shoe size
and gender, where gender = 1 for males and 0 for females.
Regression Analysis: Height Versus Shoe Size,
Gender
Coefficients
Term
Coef
SE Coef
T-Value
P-Value
Constant
55.22
1.06
52.09
0.000
Shoe Size
1.163
0.18
0.000
Gender
2.572
0.489
5.26
0.000
(a)
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Multiple R
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PART 2 CASE
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