A management consultant was hired to analyze the salary structure in a large multinational company. As part of the analysis, he interviewed 50 employees and asked each to provide his or her annual income (in thousands of dollars), the number of years of education, the number of years of experience, and his or her age.

The population regression model is defined as follows:

y= ₀ + ₁X₁+2X2+3X3+ e

y = Income ($000's), X1 = Education (years), X2 = Experience (years), and X3 = Age (years).

The excel output appears below:

Regression Analysis
Regression Statistics
R Square	0.598
Adjusted R Square	0.572
Standard Error	213.6975
Observations	50
ANOVA	Df	SS	MS	F
Regression	3	150.05	50.02	22.73
Residual	46	101.20	2.20
Total	49	251.25
	Coefficients	Standard Error	t Stat
Intercept	6.111	4.883	1.251
Education	1.261	0.351	3.593
Experience	0.836	0.390	2.144
Age	0.373	0.214	1.743

a. Write the estimated regression equation. (2 marks) b. Interpret the coefficient for the variable of Education. (2 marks)

c. Interpret the coefficient for the variable of Age. (2 marks)

d. Test the overall model at the 5% significance level. (4 marks)

e. Determine which regression coefficients are significant at the 5% level of significance. (4 marks)

f. Calculate the annual income for a 40 year old employee with 10 years of education and 5 years of experience. (3 Marks)

g. Write down another potential independent variable that could beincluded in the analysis. (1 Mark)

h. How well does the model fit the data? Use the coefficient of determination to answer the question.(2 Marks)