Question

1. Which independent variables are statistically significant in Model 2 and Model 3? Test it at 10% significance level. Provide reasons.
2. which model would you consider as a better model, Model 2 or Model 3? Use all metrics to make a determination whether a particular model is good. Provide your reasons.

Regression Statistics model 2

Standard Error of Estimate:

Multiple R           0.5580

R Square              0.3114                  Adjusted R Square   0.2821

Standard Error   249.0526              Observations     50

	df	SS	MS	F	Significance F
Regression	2	1318320.5087	659160.2544	10.6270	0.0002
Residual	47	2915279.4113	62027.2215
Total	49	4233599.9200

	Coefficients	Standard Error	t Stat	P-value	Lower 90%	Upper 90%	Lower 90%	Upper 90%
Intercept	202.9147	121.5211	1.6698	0.1016	-0.9887	406.8182	-0.9887	406.8182
Funding	10.1926	2.7092	3.7622	0.0005	5.6468	14.7384	5.6468	14.7384
School Dropout	8.4528	6.2157	1.3599	0.1803	-1.9768	18.8823	-1.9768	18.8823

Regression Statistics model 3

Standard Error of Estimate:

Multiple R           0. .5701

R Square              0.3250                   Adjusted R Square   0.2810

Standard Error   249.2410              Observations     50

	df	SS			MS		F		Significance F
Regression	3	1376029.9687			458676.6562		7.3836		0.0004
Residual	46	2857569.9513			62121.0859
Total	49	4233599.9200
	Coefficients	Standard Error		t Stat		P-value		Lower 90%			Upper 90%		Lower 90%	Upper 90%
Intercept	612.8399	232.7230		2.6333		0.0115		222.1770			1003.5028		222.1770	1003.5028
Funding	11.9794	2.7266		4.3935		0.0001		7.4024			16.5565		7.4024	16.5565
Undergraduate	0.3722	2.5706		0.1448		0.8855		-3.9429			4.6873		-3.9429	4.6873
High School	-6.0944	3.6949		-1.6494		0.1059		-12.2969			0.1080		-12.2969	0.1080

Answer 1

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