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 (10) Why is there a difference between the R square and adjusted R square values Explain (8) Is this regression equation statistically significant What is the critical value of the test statistic (Use 0 01) What does this mean (7) Which independent variables are statistically significant What does the significance level for these mean

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Question: 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

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

(10) Why is there a difference between the R-square and adjusted R-square values? Explain.
(8) Is this regression equation statistically significant? What is the critical value of the test statistic? (Use = 0.01) What does this mean?
(7) Which independent variables are statistically significant? What does the significance level for these mean?

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