Regression output of a multiple regression model

Assignment Help Basic Statistics

Reference no: EM13823822

Problem 1: The following table shows the regression output of a multiple regression model relating the beginning salaries in dollars of employees in a given company to the following predictor variables:

Sex: An indicator variable (1 = man 0 = woman)

Education: Years of schooling at the time of hire

Experience: Number of months of previous work experience

Months: Number of months with company

ANOVA Table:

Source	Sum of squares	d.f.	Mean Square	F-test
Regression	23665352	4	5916338	22.98
Residuals	22657938	88	257477

Coefficients table:

Variable	Coefficients	s.e.	t-test	p-value
Constant	3526.4	327.7	10.76	0.000
Sex	722.5	117.8	6.13	0.000
Education	90.02	24.69	3.65	0.000
Experience	1.2690	0.5877	2.16	0.034
Months	23.406	5.201	4.50	0.000
N = 93	R² = 0.515	R_a²= 0.489	S = 507.4

1. Conduct an F-test for the overall fit of the regression?

2. Is there a positive linear relationship between Salary and Experience, after accounting for the effect of the variable Sex, Education and Months?

3. What salary would you forecast for a man with 12 years of education, 10 months of experience and 15 months with company?

Problem 2: Now consider a reduced model in which Salary is regressed on Education only. The ANOVA table obtained when fitting this model is shown below. Conduct a single test to compare the full and reduced models at α = 0.05 level. What conclusion can be drawn from the result of the test?

ANOVA Table:

Source	Sum of squares	d.f.	Mean Square	F-Test
Regression	7862535	1	7862535	18.6
Residuals	38460756	91	422646

Reference no: EM13823822

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