The following linear regression model was run based on data for 500 production employees in an industry.

Earn= alpha + betaSCH+ y test 1 + o test 2

Earn = Annual salary in US $000’s SCH= number of years of formal education, test 1 and test 2 are scores on test of two dimension of intelligence that were administered by a psychologist. The computer output for the model is presented below in Table 3

Table 3 Regression Output

The regression equation is *************

Predictor	Coef	STD DEV	T-RATIO	P
Constant	7.6991	2.18118	2.74	0.006
SCH	0.9135	0.1987	*	0.000
TEST 1	3.0755	1.0052	3.06	0.002
TEST 2	0.5116	0.2912	1.76	**

S=10.23, R-sq= 0.09, R sq Adj=0.08

Analysis of Variance

Source	Df	SS	MS	F	P
Regression	3	5387.89	1795.97	-	-
Error	496	51993.04	104.82
Total	499

25. The value of * is

1. 4.60
2. 2.00
3. 1.84
4. 3.51

26. The value of ** is

1. Between 0.05 and 0.1
2. Between 0.01 and 0.025
3. Greater than 0.1
4. Between 0.025 and 0.05

27. The value of the F statistic is

1. 9.650
2. 0.104
3. 0.058
4. 17.134

28. The value associated with f statistic is

1. Between 0.01 and 0.025
2. Less than 0.001
3. Between 0.025 and 0.05
4. Between 0.01 and 0.001

29. Based on the table, which of the following is true

1. Alpha, beta and Y are significant to 5% level
2. None of the coefficients in the model are significant at the 5%level
3. Alpha, Y and O are significant to 5% level
4. All the coefficients in the model are significant at the 5% level

30. The following correlation matrix was developed using the same dataset for EARN ( annual salary) S(years of education, Test1 and Test2 ( performance on two test)

Which of the following is true

	Earn	$	Test 1	Test 2
Earn	1.000	0.272	0.235	0.196
$	0.272	1.000	0.475	0.558
Test 1	0.235	0.475	1.000	0.856
Test 2	0.196	0.558	0.856	1.000

1. Test 2 is strongly correlated with earn
2. Test 2is strongly correlated with test 1
3. Earn is strongly correlated with S
4. All of these are true