1. A sales manager was interested in determining if there is a relationship between college GPA and sales performance (number of units sold in the previous month) among salespeople hired within the last year. The estimated regression equation fit to the data was found to be significant at ? = 0.05. The 95% confidence interval for the number of units sold when GPA = 3.00 was determined to be 20.914 to 22.657. The correct interpretation is Select one: a. We can be 95% confident that the number of units sold per month by a particular salesperson with a college GPA of 3.00 is between 20.914 and 22.657 units. b. We can be 95% confident that the average number of units sold per month by salespersons with a college GPA of 3.00 is between 20.914 and 22.657 units. c. The number of units sold per month by a salesperson with a college GPA of 3.00 will be between 20.914 and 22.657 units 95% of the time. d. 95% of the time the average number of units sold per month will be between 20.914 and 22.657 units. e. We can be 95% confident that each month between 20.914 and 22.657 units will be sold. 2. As the carbon content in steel increases, its ductility tends to decrease. A researcher at a steel company measures carbon content and ductility for a sample of 15 types of steel. The estimated regression equation fit to the data was found to be significant at ? = 0.05. The 95% prediction interval for the ductility of steel with 0.5% carbon content was determined to be 0.45 to 11.59. The correct interpretation is Select one: a. We can be 95% confident that the ductility of a particular type of steel with 0.5% carbon content is between 0.45 and 11.59. b. We can be 95% confident that the average ductility of all steel with 0.5% carbon content is between 0.45 and 11.59. c. The ductility of steel with 0.5% carbon content will be between 45 and 11.59 most (95%) of the time. d. 95% of the time the average ductility of steel with 0.5% carbon content will be between 0.45 and 11.59. e. We can be 95% confident that all steel with have ductility measurements between 0.45 and 11.59. 3. An operations manager was interested in determining if there is a relationship between the amount of training received by production line workers and the time it takes for them to trouble shoot a process problem. A sample of recently trained line workers was selected. The number of hours of training time received and the time it took (in minutes) for them to trouble shoot their last process problem were captured. The regression output is shown below. At ? = .05, we will The regression equation is Trouble Shooting = 30.7 - 1.84 Training Predictor Coef SE Coef T PConstant 30.729 1.023 30.03 0.000Training -1.8360 0.1376 -13.35 0.000 S = 1.43588 R-Sq = 93.2% R-Sq(adj) = 92.7% Select one: a. conclude that the correlation between amount of training received by production line workers and the time it takes for them to trouble shoot a process problem is negative. b. conclude that the slope of the estim.

1. 1.
A sales manager was interested in determining if there is a relationship between college GPA
and sales performance (number of units sold in the previous month) among salespeople hired
within the last year. The estimated regression equation fit to the data was found to be significant
at ? = 0.05. The 95% confidence interval for the number of units sold when GPA = 3.00 was
determined to be 20.914 to 22.657. The correct interpretation is
Select one:
a. We can be 95% confident that the number of units sold per month by a particular salesperson
with a college GPA of 3.00 is between 20.914 and 22.657 units.
b. We can be 95% confident that the average number of units sold per month by salespersons
with a college GPA of 3.00 is between 20.914 and 22.657 units.
c. The number of units sold per month by a salesperson with a college GPA of 3.00 will be
between 20.914 and 22.657 units 95% of the time.
d. 95% of the time the average number of units sold per month will be between 20.914 and
22.657 units.
e. We can be 95% confident that each month between 20.914 and 22.657 units will be sold.
2.
As the carbon content in steel increases, its ductility tends to decrease. A researcher at a steel
company measures carbon content and ductility for a sample of 15 types of steel. The estimated
regression equation fit to the data was found to be significant at ? = 0.05. The 95% prediction
interval for the ductility of steel with 0.5% carbon content was determined to be 0.45 to 11.59.
The correct interpretation is
Select one:
a. We can be 95% confident that the ductility of a particular type of steel with 0.5% carbon
content is between 0.45 and 11.59.
b. We can be 95% confident that the average ductility of all steel with 0.5% carbon content is

2. between 0.45 and 11.59.
c. The ductility of steel with 0.5% carbon content will be between 45 and 11.59 most (95%) of
the time.
d. 95% of the time the average ductility of steel with 0.5% carbon content will be between 0.45
and 11.59.
e. We can be 95% confident that all steel with have ductility measurements between 0.45 and
11.59.
3.
An operations manager was interested in determining if there is a relationship between the
amount of training received by production line workers and the time it takes for them to trouble
shoot a process problem. A sample of recently trained line workers was selected. The number of
hours of training time received and the time it took (in minutes) for them to trouble shoot their
last process problem were captured. The regression output is shown below. At ? = .05, we will
The regression equation is
Trouble Shooting = 30.7 - 1.84 Training
Predictor
Coef
SE Coef
T
PConstant
30.729
1.023
30.03
0.000Training
-1.8360
0.1376
-13.35
0.000
S = 1.43588 R-Sq = 93.2% R-Sq(adj) = 92.7%

3. Select one:
a. conclude that the correlation between amount of training received by production line workers
and the time it takes for them to trouble shoot a process problem is negative.
b. conclude that the slope of the estimated regression equation is significantly different from
zero.
c. conclude that there is a significant linear relationship between amount of training received by
production line workers and the time it takes for them to trouble shoot a process problem.
d. both B and C.
e. all of the above (A, B and C).
1.
A sales manager was interested in determining if there is a relationship between college GPA
and sales performance (number of units sold in the previous month) among salespeople hired
within the last year. The estimated regression equation fit to the data was found to be significant
at ? = 0.05. The 95% confidence interval for the number of units sold when GPA = 3.00 was
determined to be 20.914 to 22.657. The correct interpretation is
1.
A sales manager was interested in determining if there is a relationship between college GPA
and sales performance (number of units sold in the previous month) among salespeople hired
within the last year. The estimated regression equation fit to the data was found to be significant
at ? = 0.05. The 95% confidence interval for the number of units sold when GPA = 3.00 was
determined to be 20.914 to 22.657. The correct interpretation is
Select one:
a. We can be 95% confident that the number of units sold per month by a particular salesperson
with a college GPA of 3.00 is between 20.914 and 22.657 units.
b. We can be 95% confident that the average number of units sold per month by salespersons

4. with a college GPA of 3.00 is between 20.914 and 22.657 units.
c. The number of units sold per month by a salesperson with a college GPA of 3.00 will be
between 20.914 and 22.657 units 95% of the time.
d. 95% of the time the average number of units sold per month will be between 20.914 and
22.657 units.
e. We can be 95% confident that each month between 20.914 and 22.657 units will be sold.
2.
As the carbon content in steel increases, its ductility tends to decrease. A researcher at a steel
company measures carbon content and ductility for a sample of 15 types of steel. The estimated
regression equation fit to the data was found to be significant at ? = 0.05. The 95% prediction
interval for the ductility of steel with 0.5% carbon content was determined to be 0.45 to 11.59.
The correct interpretation is
Select one:
a. We can be 95% confident that the ductility of a particular type of steel with 0.5% carbon
content is between 0.45 and 11.59.
b. We can be 95% confident that the average ductility of all steel with 0.5% carbon content is
between 0.45 and 11.59.
c. The ductility of steel with 0.5% carbon content will be between 45 and 11.59 most (95%) of
the time.
d. 95% of the time the average ductility of steel with 0.5% carbon content will be between 0.45
and 11.59.
e. We can be 95% confident that all steel with have ductility measurements between 0.45 and
11.59.
3.
An operations manager was interested in determining if there is a relationship between the
amount of training received by production line workers and the time it takes for them to trouble
shoot a process problem. A sample of recently trained line workers was selected. The number of
hours of training time received and the time it took (in minutes) for them to trouble shoot their

5. last process problem were captured. The regression output is shown below. At ? = .05, we will
The regression equation is
Trouble Shooting = 30.7 - 1.84 Training
Predictor
Coef
SE Coef
T
PConstant
30.729
1.023
30.03
0.000Training
-1.8360
0.1376
-13.35
0.000
S = 1.43588 R-Sq = 93.2% R-Sq(adj) = 92.7%
Select one:
a. conclude that the correlation between amount of training received by production line workers
and the time it takes for them to trouble shoot a process problem is negative.
b. conclude that the slope of the estimated regression equation is significantly different from
zero.
c. conclude that there is a significant linear relationship between amount of training received by
production line workers and the time it takes for them to trouble shoot a process problem.
d. both B and C.
e. all of the above (A, B and C).

6. Select one:
a. We can be 95% confident that the number of units sold per month by a particular salesperson
with a college GPA of 3.00 is between 20.914 and 22.657 units.
b. We can be 95% confident that the average number of units sold per month by salespersons
with a college GPA of 3.00 is between 20.914 and 22.657 units.
c. The number of units sold per month by a salesperson with a college GPA of 3.00 will be
between 20.914 and 22.657 units 95% of the time.
d. 95% of the time the average number of units sold per month will be between 20.914 and
22.657 units.
e. We can be 95% confident that each month between 20.914 and 22.657 units will be sold.
2.
As the carbon content in steel increases, its ductility tends to decrease. A researcher at a steel
company measures carbon content and ductility for a sample of 15 types of steel. The estimated
regression equation fit to the data was found to be significant at ? = 0.05. The 95% prediction
interval for the ductility of steel with 0.5% carbon content was determined to be 0.45 to 11.59.
The correct interpretation is
Select one:
a. We can be 95% confident that the ductility of a particular type of steel with 0.5% carbon
content is between 0.45 and 11.59.
b. We can be 95% confident that the average ductility of all steel with 0.5% carbon content is
between 0.45 and 11.59.
c. The ductility of steel with 0.5% carbon content will be between 45 and 11.59 most (95%) of
the time.
d. 95% of the time the average ductility of steel with 0.5% carbon content will be between 0.45
and 11.59.
e. We can be 95% confident that all steel with have ductility measurements between 0.45 and
11.59.

7. 3.
An operations manager was interested in determining if there is a relationship between the
amount of training received by production line workers and the time it takes for them to trouble
shoot a process problem. A sample of recently trained line workers was selected. The number of
hours of training time received and the time it took (in minutes) for them to trouble shoot their
last process problem were captured. The regression output is shown below. At ? = .05, we will
The regression equation is
Trouble Shooting = 30.7 - 1.84 Training
Predictor
Coef
SE Coef
T
PConstant
30.729
1.023
30.03
0.000Training
-1.8360
0.1376
-13.35
0.000
S = 1.43588 R-Sq = 93.2% R-Sq(adj) = 92.7%
Select one:
a. conclude that the correlation between amount of training received by production line workers
and the time it takes for them to trouble shoot a process problem is negative.
b. conclude that the slope of the estimated regression equation is significantly different from
zero.
c. conclude that there is a significant linear relationship between amount of training received by
production line workers and the time it takes for them to trouble shoot a process problem.
d. both B and C.

8. e. all of the above (A, B and C).
a. We can be 95% confident that the number of units sold per month by a particular salesperson
with a college GPA of 3.00 is between 20.914 and 22.657 units.
b. We can be 95% confident that the average number of units sold per month by salespersons
with a college GPA of 3.00 is between 20.914 and 22.657 units.
c. The number of units sold per month by a salesperson with a college GPA of 3.00 will be
between 20.914 and 22.657 units 95% of the time.
d. 95% of the time the average number of units sold per month will be between 20.914 and
22.657 units.
e. We can be 95% confident that each month between 20.914 and 22.657 units will be sold.
2.
As the carbon content in steel increases, its ductility tends to decrease. A researcher at a steel
company measures carbon content and ductility for a sample of 15 types of steel. The estimated
regression equation fit to the data was found to be significant at ? = 0.05. The 95% prediction
interval for the ductility of steel with 0.5% carbon content was determined to be 0.45 to 11.59.
The correct interpretation is
Select one:
a. We can be 95% confident that the ductility of a particular type of steel with 0.5% carbon
content is between 0.45 and 11.59.
b. We can be 95% confident that the average ductility of all steel with 0.5% carbon content is
between 0.45 and 11.59.
c. The ductility of steel with 0.5% carbon content will be between 45 and 11.59 most (95%) of
the time.
d. 95% of the time the average ductility of steel with 0.5% carbon content will be between 0.45
and 11.59.

9. e. We can be 95% confident that all steel with have ductility measurements between 0.45 and
11.59.
3.
An operations manager was interested in determining if there is a relationship between the
amount of training received by production line workers and the time it takes for them to trouble
shoot a process problem. A sample of recently trained line workers was selected. The number of
hours of training time received and the time it took (in minutes) for them to trouble shoot their
last process problem were captured. The regression output is shown below. At ? = .05, we will
The regression equation is
Trouble Shooting = 30.7 - 1.84 Training
Predictor
Coef
SE Coef
T
PConstant
30.729
1.023
30.03
0.000Training
-1.8360
0.1376
-13.35
0.000
S = 1.43588 R-Sq = 93.2% R-Sq(adj) = 92.7%
Select one:
a. conclude that the correlation between amount of training received by production line workers
and the time it takes for them to trouble shoot a process problem is negative.
b. conclude that the slope of the estimated regression equation is significantly different from

10. zero.
c. conclude that there is a significant linear relationship between amount of training received by
production line workers and the time it takes for them to trouble shoot a process problem.
d. both B and C.
e. all of the above (A, B and C).
2.
As the carbon content in steel increases, its ductility tends to decrease. A researcher at a steel
company measures carbon content and ductility for a sample of 15 types of steel. The estimated
regression equation fit to the data was found to be significant at ? = 0.05. The 95% prediction
interval for the ductility of steel with 0.5% carbon content was determined to be 0.45 to 11.59.
The correct interpretation is
2.
As the carbon content in steel increases, its ductility tends to decrease. A researcher at a steel
company measures carbon content and ductility for a sample of 15 types of steel. The estimated
regression equation fit to the data was found to be significant at ? = 0.05. The 95% prediction
interval for the ductility of steel with 0.5% carbon content was determined to be 0.45 to 11.59.
The correct interpretation is
Select one:
a. We can be 95% confident that the ductility of a particular type of steel with 0.5% carbon
content is between 0.45 and 11.59.
b. We can be 95% confident that the average ductility of all steel with 0.5% carbon content is
between 0.45 and 11.59.
c. The ductility of steel with 0.5% carbon content will be between 45 and 11.59 most (95%) of
the time.
d. 95% of the time the average ductility of steel with 0.5% carbon content will be between 0.45
and 11.59.
e. We can be 95% confident that all steel with have ductility measurements between 0.45 and

11. 11.59.
3.
An operations manager was interested in determining if there is a relationship between the
amount of training received by production line workers and the time it takes for them to trouble
shoot a process problem. A sample of recently trained line workers was selected. The number of
hours of training time received and the time it took (in minutes) for them to trouble shoot their
last process problem were captured. The regression output is shown below. At ? = .05, we will
The regression equation is
Trouble Shooting = 30.7 - 1.84 Training
Predictor
Coef
SE Coef
T
PConstant
30.729
1.023
30.03
0.000Training
-1.8360
0.1376
-13.35
0.000
S = 1.43588 R-Sq = 93.2% R-Sq(adj) = 92.7%
Select one:
a. conclude that the correlation between amount of training received by production line workers
and the time it takes for them to trouble shoot a process problem is negative.
b. conclude that the slope of the estimated regression equation is significantly different from
zero.

12. c. conclude that there is a significant linear relationship between amount of training received by
production line workers and the time it takes for them to trouble shoot a process problem.
d. both B and C.
e. all of the above (A, B and C).
Select one:
a. We can be 95% confident that the ductility of a particular type of steel with 0.5% carbon
content is between 0.45 and 11.59.
b. We can be 95% confident that the average ductility of all steel with 0.5% carbon content is
between 0.45 and 11.59.
c. The ductility of steel with 0.5% carbon content will be between 45 and 11.59 most (95%) of
the time.
d. 95% of the time the average ductility of steel with 0.5% carbon content will be between 0.45
and 11.59.
e. We can be 95% confident that all steel with have ductility measurements between 0.45 and
11.59.
3.
An operations manager was interested in determining if there is a relationship between the
amount of training received by production line workers and the time it takes for them to trouble
shoot a process problem. A sample of recently trained line workers was selected. The number of
hours of training time received and the time it took (in minutes) for them to trouble shoot their
last process problem were captured. The regression output is shown below. At ? = .05, we will
The regression equation is
Trouble Shooting = 30.7 - 1.84 Training
Predictor

13. Coef
SE Coef
T
PConstant
30.729
1.023
30.03
0.000Training
-1.8360
0.1376
-13.35
0.000
S = 1.43588 R-Sq = 93.2% R-Sq(adj) = 92.7%
Select one:
a. conclude that the correlation between amount of training received by production line workers
and the time it takes for them to trouble shoot a process problem is negative.
b. conclude that the slope of the estimated regression equation is significantly different from
zero.
c. conclude that there is a significant linear relationship between amount of training received by
production line workers and the time it takes for them to trouble shoot a process problem.
d. both B and C.
e. all of the above (A, B and C).
a. We can be 95% confident that the ductility of a particular type of steel with 0.5% carbon
content is between 0.45 and 11.59.
b. We can be 95% confident that the average ductility of all steel with 0.5% carbon content is
between 0.45 and 11.59.
c. The ductility of steel with 0.5% carbon content will be between 45 and 11.59 most (95%) of

14. the time.
d. 95% of the time the average ductility of steel with 0.5% carbon content will be between 0.45
and 11.59.
e. We can be 95% confident that all steel with have ductility measurements between 0.45 and
11.59.
3.
An operations manager was interested in determining if there is a relationship between the
amount of training received by production line workers and the time it takes for them to trouble
shoot a process problem. A sample of recently trained line workers was selected. The number of
hours of training time received and the time it took (in minutes) for them to trouble shoot their
last process problem were captured. The regression output is shown below. At ? = .05, we will
The regression equation is
Trouble Shooting = 30.7 - 1.84 Training
Predictor
Coef
SE Coef
T
PConstant
30.729
1.023
30.03
0.000Training
-1.8360
0.1376
-13.35
0.000
S = 1.43588 R-Sq = 93.2% R-Sq(adj) = 92.7%
Select one:

15. a. conclude that the correlation between amount of training received by production line workers
and the time it takes for them to trouble shoot a process problem is negative.
b. conclude that the slope of the estimated regression equation is significantly different from
zero.
c. conclude that there is a significant linear relationship between amount of training received by
production line workers and the time it takes for them to trouble shoot a process problem.
d. both B and C.
e. all of the above (A, B and C).
3.
An operations manager was interested in determining if there is a relationship between the
amount of training received by production line workers and the time it takes for them to trouble
shoot a process problem. A sample of recently trained line workers was selected. The number of
hours of training time received and the time it took (in minutes) for them to trouble shoot their
last process problem were captured. The regression output is shown below. At ? = .05, we will
The regression equation is
Trouble Shooting = 30.7 - 1.84 Training
Predictor
Coef
SE Coef
T
PConstant
30.729
1.023
30.03
0.000Training
-1.8360
0.1376

16. -13.35
0.000
S = 1.43588 R-Sq = 93.2% R-Sq(adj) = 92.7%
3.
An operations manager was interested in determining if there is a relationship between the
amount of training received by production line workers and the time it takes for them to trouble
shoot a process problem. A sample of recently trained line workers was selected. The number of
hours of training time received and the time it took (in minutes) for them to trouble shoot their
last process problem were captured. The regression output is shown below. At ? = .05, we will
The regression equation is
Trouble Shooting = 30.7 - 1.84 Training
Predictor
Coef
SE Coef
T
PConstant
30.729
1.023
30.03
0.000Training
-1.8360
0.1376
-13.35
0.000
Coef
SE Coef
T
P
30.729
1.023
30.03
0.000
-1.8360

17. 0.1376
-13.35
0.000
S = 1.43588 R-Sq = 93.2% R-Sq(adj) = 92.7%
Select one:
a. conclude that the correlation between amount of training received by production line workers
and the time it takes for them to trouble shoot a process problem is negative.
b. conclude that the slope of the estimated regression equation is significantly different from
zero.
c. conclude that there is a significant linear relationship between amount of training received by
production line workers and the time it takes for them to trouble shoot a process problem.
d. both B and C.
e. all of the above (A, B and C).
Select one:
a. conclude that the correlation between amount of training received by production line workers
and the time it takes for them to trouble shoot a process problem is negative.
b. conclude that the slope of the estimated regression equation is significantly different from
zero.
c. conclude that there is a significant linear relationship between amount of training received by
production line workers and the time it takes for them to trouble shoot a process problem.
d. both B and C.
e. all of the above (A, B and C).
a. conclude that the correlation between amount of training received by production line workers
and the time it takes for them to trouble shoot a process problem is negative.
b. conclude that the slope of the estimated regression equation is significantly different from
zero.
c. conclude that there is a significant linear relationship between amount of training received by
production line workers and the time it takes for them to trouble shoot a process problem.
d. both B and C.
e. all of the above (A, B and C).

18. Predictor
Coef
SE Coef
T
PConstant
30.729
1.023
30.03
0.000Training
-1.8360
0.1376
-13.35
0.000
Solution
1.a
2.a
3.e