The following sample observations were randomly selected. 
X : 4 5 3 6 10 
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(1) 
Fill in the blanks below: (Round your answers to 2 decimal places.) 



correlation between X and Y. 
(3) 
Fill in the blanks. (Round your answer to the nearest whole number.) 
The coefficient of determination obtained here indicates X accounts for approximately relationship between X and Y. The coefficient of determination is is the dependent variable. 
(c) 
Determine the correlation coefficient. (Round your answer to 2 decimal places.) 
Coefficient of correlation 
correlation between the variables. 
4) The production department of Celltronics International wants to explore the relationship between the number of employees who assemble a subassembly and the number produced. As an experiment, two employees were assigned to assemble the subassemblies. They produced 15 during a onehour period. Then four employees assembled them. They produced 25 during a onehour period. The complete set of paired observations follows. 
Number of 
OneHour 
2 
15 
4 
25 
1 
10 
5 
40 
3 
30 

The dependent variable is production; that is, it is assumed that different levels of production result from a different number of employees. 
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(b) 
A scatter diagram is provided below. Based on it, does there appear to be any relationship between the number of assemblers and production? 



, as the number of assemblers, so does the production. 
(c) 
Compute the coefficient of correlation. (Negative amounts should be indicated by a minus sign. Round s_{x}, s_{y} and r to 3 decimal places.) 
X 
Y 
( )^{2} 
( )^{2} 
( )( ) 

2 
15 
is the independent variable and is the dependent variable. 
(b1) 
Determine the coefficient of correlation. (Negative amounts should be indicated by a minus sign. Round your answers to 3 decimal places.) 
X 
Y 
( )^{2} 
( )^{2} 
( )( ) 

9.0 
8.1 
correlation between age of car and selling price. So, H_{o}. Weconclude that the correlation in the population is 
7) The following hypotheses are given. 


A random sample of 15 paired observations have a correlation of −.46. Can we conclude that the correlation in the population is less than zero? Use the .05 significance level. (Negative amount should be indicated by a minus sign. Round your answer to 3 decimal places.) 
Reject H_{0} if t < −1.771 
t 
= 
H_{o}. 
8) The following sample observations were randomly selected. 
Click here for the Excel Data File 


X: 
5 
3 
6 
3 
4 
4 
6 
8 
Y: 
13 
15 
7 
12 
13 
11 
9 
5 

(a) 
Determine the regression equation. (Negative amounts should be indicated by a minus sign. Round your answers to 3 decimal places.) 
X 
Y 
()^{2} 
()^{2} 
( )( ) 

5 
13 
[removed] 
2.375 
[removed] 
5.641 
[removed] 
3 
15 
−1.875 
[removed] 
3.516 
[removed] 
−8.203 
6 
7 
[removed] 
[removed] 
[removed] 
13.141 
−4.078 
3 
12 
−1.875 
1.375 
[removed] 
[removed] 
[removed] 
4 
13 
−0.875 
[removed] 
0.766 
[removed] 
−2.078 
4 
11 
[removed] 
0.375 
[removed] 
0.141 
[removed] 
6 
9 
1.125 
−1.625 
[removed] 
[removed] 
[removed] 
8 
5 
[removed] 
[removed] 
[removed] 
31.641 
−17.578 
[removed] 
[removed] 


[removed] 
[removed] 
[removed] 


= 
[removed] 


= 
[removed] 

s_{x} 
= 
[removed] 
s_{y} 
= 
[removed] 

r 
= 
[removed] 
b 
= 
[removed] 

a 
= 
[removed] 
Y’ = [removed]+ [removed]X 
(b) 
Determine the value of when X is 7. (Round your answer to 3 decimal places.) 



[removed] 
9) Bradford Electric Illuminating Company is studying the relationship between kilowatthours (thousands) used and the number of rooms in a private singlefamily residence. A random sample of 10 homes yielded the following. 
Number of Rooms 
KilowattHours (thousands) 
Number of Rooms 
KilowattHours (thousands) 

12 

9 

8 

6 

9 

7 

10 

8 

14 

10 

10 

10 

6 

5 

5 

4 

10 

8 

7 

7 


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(a) 
Determine the regression equation. (Round your answers to 3 decimal places.) 
= [removed] + [removed]X 
(b) 
Determine the number of kilowatthours, in thousands, for a sixroom house.(Round your answer to 3 decimal places.) 
Number of kilowatthours 
[removed] 
Number of 
Sales 
Number of 
Sales 

14 

24 

23 

30 

12 

14 

48 

90 

20 

28 

50 

85 

16 

30 

55 

120 

46 

80 

50 

110 


Click here for the Excel Data File 
(a) 
Determine the regression equation. (Negative amounts should be indicated by a minus sign.Do not round intermediate calculations. Round final answers to 2 decimal places.) 
X 
Y 
( ) ^{2} 
( )^{2} 
( )( ) 

14 
[removed] 
[removed] 
[removed] 
376.36 
1376.41 
719.74 
12 
14 
−21.4 
−47.1 
[removed] 
[removed] 
[removed] 
20 
[removed] 
−13.4 
[removed] 
179.56 
[removed] 
443.54 
16 
30 
[removed] 
−31.1 
[removed] 
967.21 
[removed] 
46 
[removed] 
12.6 
[removed] 
[removed] 
357.21 
[removed] 
23 
[removed] 
−10.4 
[removed] 
[removed] 
967.21 
[removed] 
48 
90 
[removed] 
28.9 
213.16 
[removed] 
421.94 
50 
85 
[removed] 
23.9 
275.56 
[removed] 
396.74 
55 
[removed] 
[removed] 
[removed] 
466.56 
3469.21 
1,272.24 
50 
110.0 
16.6 
48.9 
[removed] 
[removed] 
[removed] 
[removed] 
[removed] 


[removed] 
[removed] 
[removed] 


= 
[removed] 


= 
[removed] 

s_{x} 
= 
[removed] 
s_{y} 
= 
[removed] 

r 
= 
[removed] 
b =[removed] 
a = [removed] 
Y’ = [removed]+ [removed]X 
(b) 
Determine the estimated sales if 40 contacts are made.(Do not round intermediate calculations. Round final answers to 2 decimal places.) 
[removed] 