Below is the Excel summary output from multiple regression situation in which you are attempting to predict income on the basis of eight different independent variables.

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.5809
R Square	0.3374
Adjusted R Square	0.3180
Standard Error	33250
Observations	282
ANOVA
df	SS	MS	F	Significance F
Regression	8	153,716,984,625	19,214,623,708	17.38
Residual	273	301,813,647,689	1,105,544,497
Total	281	455,530632,314
Coefficients	Standard Error	t stat	P-Value
Intercept	-51785	19259	-2.69	0.0076
Age	461	237	1.95	0.0527
Education	4101	848	4.84	0.0000
Hours worked	620	173	3.59	0.0004
Spouse hours	-862	185	-4.67	4.71E-06
Occupations with prestige	641	176	3.64	0.0003
CHILDREN	-331	1522	-0.22	0.8279
EARNERS	687	2929	0.23	0.8147
Years in Job	330	237	1.39	0.1649

Why is there a difference between the R-square and adjusted R-square values? Explain.

Is this regression equation statistically significant? What is the critical value of the test statistic? (Use = 0.01) What does this mean?

Which independent variables are statistically significant? What does the significance level for these mean?

Please show work