years Xi bonus Yi XiYi Xi2 4 5.7 22.8 16 2 3.5 7 4 7.4 10.1 74.74 54.76 5 9 45 25 2 2.7 5.4 4 12 12 144 144   Question 25  Are years of service and annual bonuses related?  The annual bonuses of 6 randomly selected employees (measured in “thousands of dollars”) along their their respective years of service for the company.  Suppose we estimate a linear regression using the Ordinary Least Squares technique of the form: Bonusi = b0 + b1(yearsi) where the subscript i indicates the ith employee Using your excel output from this regression, what is the correct decision using the p value method for the slope test (assume an alpha level of .05) H0:  B1 = 0 (not a linear relationship) H1:  B1 ≠ 0 (is a linear relationship)     a)  a.  fail to reject the null hypothesis, there is insufficient evidence of a linear relationship   b)  b.  fail to reject the null hypothesis, there is sufficient evidence of a linear relationship   c)  c.  reject the null hypothesis, there is sufficient evidence of a linear relationship   d)  d.  reject the null hypothesis, there is insufficient evidence of a linear relationship

MATLAB: An Introduction with Applications
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Author:Amos Gilat
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years Xi

bonus Yi

XiYi

Xi2

4

5.7

22.8

16

2

3.5

7

4

7.4

10.1

74.74

54.76

5

9

45

25

2

2.7

5.4

4

12

12

144

144

 

Question 25  Are years of service and annual bonuses related?  The annual bonuses of 6 randomly selected employees (measured in “thousands of dollars”) along their their respective years of service for the company.  Suppose we estimate a linear regression using the Ordinary Least Squares technique of the form:

Bonusi = b0 + b1(yearsi)

where the subscript i indicates the ith employee

Using your excel output from this regression, what is the correct decision using the p value method for the slope test (assume an alpha level of .05)

H0:  B1 = 0 (not a linear relationship)

H1:  B1 ≠ 0 (is a linear relationship)

 

 

a) 

a.  fail to reject the null hypothesis, there is insufficient evidence of a linear relationship

 

b) 

b.  fail to reject the null hypothesis, there is sufficient evidence of a linear relationship

 

c) 

c.  reject the null hypothesis, there is sufficient evidence of a linear relationship

 

d) 

d.  reject the null hypothesis, there is insufficient evidence of a linear relationship

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