Question

Consider the following computer output of a multiple regression analysis relating annual salary to years of education and years of work experience.

Regression Statistics
Multiple R	0.7338
R Square	0.5384
Adjusted R Square	0.5183
Standard Error	2139.0907
Observations	49

ANOVA
	df	SS	MS	F	Significance F
Regression	2	245,472,093.5833	122,736,046.7917	26.8234	1.9E-08
Residual	46	210,482,624.6208	4,575,709.2309
Total	48	455,954,718.2041

	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	14275.75637	2,530.4400	5.6416	0.000000994	9182.2448	19,369.2679
Education (Years)	2350.2675	338.3625	6.9460	0.000000011	1669.1791	3031.3559
Experience (Years)	833.2984	392.8512	2.1212	0.039325236	42.5299	1624.0669

Step 1 of 2:  

What would be your expected salary with no education and no experience?

Step 2 of 2:

How much would you expect your salary to increase if you had one more year of education?

Answer 1

Step 1 of 2:  

What would be your expected salary with no education and no experience?

The expected salary with no education and no experience would be $14275.76.

From the given output of regression model, the value for the y-intercept is given as 14275.76, which means when a person have no any education and without any experience, then expected salary would be $14275.76.

Step 2 of 2:

How much would you expect your salary to increase if you had one more year of education?

We expected salary to increase by $2350.27 if we have one more year of education.

From given regression output, the slope for the variable year of education is given as 2350.27 which means, there is an increment of $2350.27 in the dependent variable salary when there is an increment of 1 year in education.