The multiple regression relationship of SBP(Y) to AGE(X₁), SMK (X₂), and QUET(X₃) are studied. Use the following tables to answer questions:

Model 1: Regression of SBP on AGE:

Source	DF	Sum of Squares	Mean Square	F Value	Pr>F
Model	1	89.5738	89.5738	0.03	0.8633
Error	62	185893.7856	2998.2869
Corrected Total	63	185983.3594

Parameter	Estimate	Standard Error	tValue	Pr>|t|
Intercept	36.49808352	6.94661760	5.25	<.0001
age	0.00933174	0.05398941	0.17	0.8633

Model II: Regression of SBP on AGE and SMK:

The GLM Procedure

Dependent Variable: sbp

Source	DF	Sum of Squares	Mean Square	F Value	Pr>F
Model	2	13257.8049	6628.9025	2.34	0.1048
Error	61	172725.5545	2831.5665
Corrected Total	63	185983.3594

R-Square	Coeff Var	Root MSE	sbpMean
0.071285	144.9807	53.21247	36.70313

Parameter	Estimate	Standard Error	tValue	Pr>|t|
Intercept	50.11197806	9.24259271	5.42	<.0001
age	-0.00582083	0.05293530	-0.11	0.9128
smk	-0.14325612	0.06642979	-2.16	0.0350

Model III: Regression of SBP on AGE,SMK and QUET:

Source	Df	Sum of Squares	Mean square	F-value	Pr>F
Model	3	4889.83	1629.94	29.71	<.0001
Error	28	1536.14	54.86
Correct Total	31	6425.97

Source	Estimate	Standard Error	t-value	Pr>F
Intercept	45.10	10.76	4.19	0.0003
Age	1.21	0.32	3.75	0.0008
SMK	9.95	2.66	3.74	0.0008
QUET	8.59	4.49	1.91	0.0664

1. Write the estimate regression models:

Model 1:

Model 2:

Model 3:

1. Conduct overall test F -test for significant regression for the three models( Use ANOVA table). State the null and alternative hypotheses for each test and interpreter results

Model 1:

Model 2:

Model 3:

3. Based on your results which of the three models is the best? (explain reasoning)(2 points)