Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card
Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card
8th Edition
ISBN: 9781464158933
Author: David S. Moore, George P. McCabe, Bruce A. Craig
Publisher: W. H. Freeman
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Chapter 11, Problem 41E
To determine

To test: A regression to predict the LVO using LOC.

Expert Solution
Check Mark

Answer to Problem 41E

Solution: The regression equation is

LVO=5.21+0.441 LOC

with S=0.4089 and R2=30.8%.

The ANOVA is given below:

Degrees of freedom

Sum of Squares

Mean sum of squares

F-statistic

P-value

Regression

1

2.1556

2.1556

12.89

0.001

Residual

29

4.8499

0.1672

Total

30

7.0055

Explanation of Solution

Calculation: To perform the regression analysis to predict L VO, Minitab is used. The steps to be followed are as follows:

Step 1: Open the Minitab worksheet.

Step 2: Go to Stat > Regression > Regression.

Step 3: Select “ LVO ” in Response and select “LOC” in Predictors.

Step 4: Go to graph and select residual versus fits.

Step 5: Click “OK.”

The estimated regression equation is

LVO=5.21+0.441 LOC

with F=12.89 and P-value=0.001.

Conclusion: Since the P-value is less than 0.05, the result is significant. The variation in the variable VO is 30.8%.

To determine

To test: A regression to predict the LVO using LTRAP.

Expert Solution
Check Mark

Answer to Problem 41E

Solution: The regression equation is

LVO=5.09+0.645 LTRAP

with S=0.3673 and R2=44.1%.

The ANOVA is given below:

Degrees of freedom

Sum of Squares

Mean sum of squares

F-statistic

P-value

Regression

1

3.0915

3.0915

22.91

0.000

Residual

29

3.9140

0.1350

Total

30

7.0055

Explanation of Solution

Calculation: To perform the regression analysis to predict LVO, Minitab is used. The steps to be followed are as follows:

Step 1: Open the Minitab worksheet.

Step 2: Go to Stat > Regression > Regression.

Step 3: Select “ LVO ” in Response and select “LTRAP” in Predictors.

Step 4: Go to graph and select residual versus fits.

Step 5: Click “OK.”

The estimated regression equation is

LVO=5.09+0.645 LTRAP

with F=22.19 and P-value=0.000.

Conclusion: Since the P-value is less than 0.05, the result is significant. The variation in the variable VO is 44.1%.

To determine

To test: A regression to predict the LVO using LOC and LTRAP.

Expert Solution
Check Mark

Answer to Problem 41E

Solution: The regression equation is

LVO=5.04+0.057LOC+ 0.590LTRAP

with S=0.373250 and R2=44.3%.

The ANOVA is given below:

Degrees of freedom

Sum of Squares

Mean sum of squares

F-statistic

P-value

Regression

2

3.1047

1.5524

11.14

0.000

Residual

28

3.9008

0.1393

Total

30

7.0055

Explanation of Solution

Calculation: To perform the regression analysis to predict LVO, Minitab is used. The steps to be followed are as follows:

Step 1: Open the Minitab worksheet.

Step 2: Go to Stat > Regression > Regression.

Step 3: Select “ LVO ” in Response and select “LOC and LTRAP” in Predictors.

Step 4: Go to graph and select residual versus fits.

Step 5: Click “OK.”

The estimated regression equation is

LVO=5.04+0.057LOC+ 0.590LTRAP

with F=11.14 and P-value=0.000. For OC, t = 0.31 and P-value=0.76, and for TRAP, t = 2.61 and P-value=0.014.

Conclusion: Since the P-value is less than 0.05 for LTRAP, the result is significant for LTRAP. The variation in the variable LVO is 44.3%.

To determine

To test: A regression to predict the LVO using LOC, LTRAP, and LVO+.

Expert Solution
Check Mark

Answer to Problem 41E

Solution: The regression equation is

LVO=1.740.233 LOC+ 0.0111 LTRAP+0.824 LVO+

with S=0.2621 and R2=73.5%.

The ANOVA is given below:

Degrees of freedom

Sum of Squares

Mean sum of squares

F-statistic

P-value

Regression

3

5.1494

1.7165

24.97

0.000

Residual

27

1.8562

0.0687

Total

30

7.0055

Explanation of Solution

Calculation: To perform the regression analysis to predict LVO, Minitab is used. The steps to be followed are as follows:

Step 1: Open the Minitab worksheet.

Step 2: Go to Stat > Regression > Regression.

Step 3: Select “ LVO ” in Response and select “LOC, LTRAP and LVO+ ” in Predictors.

Step 4: Go to graph and select residual versus fits.

Step 5: Click “OK.”

The estimated regression equation is

LVO=1.740.233 LOC+ 0.0111 LTRAP+0.824 LVO+

with F=24.97 and P-value=0.000.

Conclusion: Since the P-value is less than 0.05, the result is significant. The variation in the variable LVO is 73.5%.

To determine

To test: A regression to predict the LVO using LOC and LVO+.

Expert Solution
Check Mark

Answer to Problem 41E

Solution: The Regression equation is

LVO=1.310.188 LOC+0.890 LVO+

with S=0.2611 and R2=72.8%.

The ANOVA is given below:

Degrees of freedom

Sum of Squares

Mean sum of squares

F-statistic

P-value

Regression

2

5.0965

2.5483

37.38

0.000

Residual

28

1.9090

0.0682

Total

30

7.0055

Explanation of Solution

Calculation: To perform the regression analysis to predict LVO, Minitab is used. The steps to be followed are as follows:

Step 1: Open the Minitab worksheet.

Step 2: Go to Stat > Regression > Regression.

Step 3: Select “ LVO ” in Response and select “LOC and LVO+ ” in Predictors.

Step 4: Go to graph and select residual versus fits.

Step 5: Click “OK.”

The estimated regression equation is

LVO=1.310.188 LOC+0.890 LVO+

with F=37.38 and P-value=0.000.

Conclusion: Since the P-value is less than 0.05, the result is significant. The variation in the variable LVO is 72.8%.

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