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

Question

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Answer 1

Question

Chapter 11, Problem 45E

To determine

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

Expert Solution

Answer to Problem 45E

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

Answer to Problem 45E

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

Answer to Problem 45E

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

Answer to Problem 45E

Solution: The regression equation is

LVO−=1.74−0.233 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−=1.74−0.233 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

Answer to Problem 45E

Solution: The Regression equation is

LVO−=1.31−0.188 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−=1.31−0.188 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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Answer 2

Question

Chapter 11, Problem 45E

To determine

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

Expert Solution

Answer to Problem 45E

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

Answer to Problem 45E

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

Answer to Problem 45E

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

Answer to Problem 45E

Solution: The regression equation is

LVO−=1.74−0.233 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−=1.74−0.233 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

Answer to Problem 45E

Solution: The Regression equation is

LVO−=1.31−0.188 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−=1.31−0.188 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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Answer 3

Question

Chapter 11, Problem 45E

To determine

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

Expert Solution

Answer to Problem 45E

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

Answer to Problem 45E

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

Answer to Problem 45E

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

Answer to Problem 45E

Solution: The regression equation is

LVO−=1.74−0.233 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−=1.74−0.233 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

Answer to Problem 45E

Solution: The Regression equation is

LVO−=1.31−0.188 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−=1.31−0.188 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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Answer 4

Question

Chapter 11, Problem 45E

To determine

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

Expert Solution

Answer to Problem 45E

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

Answer to Problem 45E

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

Answer to Problem 45E

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

Answer to Problem 45E

Solution: The regression equation is

LVO−=1.74−0.233 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−=1.74−0.233 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

Answer to Problem 45E

Solution: The Regression equation is

LVO−=1.31−0.188 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−=1.31−0.188 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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Answer 5

Chapter 11, Problem 45E

To determine

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

Expert Solution

Answer to Problem 45E

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

Answer to Problem 45E

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

Answer to Problem 45E

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

Answer to Problem 45E

Solution: The regression equation is

LVO−=1.74−0.233 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−=1.74−0.233 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

Answer to Problem 45E

Solution: The Regression equation is

LVO−=1.31−0.188 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−=1.31−0.188 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%.

Answer 6

Chapter 11, Problem 45E

To determine

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

Expert Solution

Answer to Problem 45E

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%.

Answer 7

Chapter 11, Problem 45E

To determine

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

Answer 8

Expert Solution

Answer to Problem 45E

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

Answer 9

Expert Solution

Answer 10

Expert Solution

Answer 11

Expert Solution

Answer 12

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%.

Answer 13

To determine

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

Expert Solution

Answer to Problem 45E

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%.

Answer 14

To determine

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

Answer 15

Expert Solution

Answer to Problem 45E

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

Answer 16

Expert Solution

Answer 17

Expert Solution

Answer 18

Expert Solution

Answer 19

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%.

Answer 20

To determine

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

Expert Solution

Answer to Problem 45E

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%.

Answer 21

To determine

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

Answer 22

Expert Solution

Answer to Problem 45E

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

Answer 23

Expert Solution

Answer 24

Expert Solution

Answer 25

Expert Solution

Answer 26

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%.

Answer 27

To determine

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

Expert Solution

Answer to Problem 45E

Solution: The regression equation is

LVO−=1.74−0.233 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−=1.74−0.233 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%.

Answer 28

To determine

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

Answer 29

Expert Solution

Answer to Problem 45E

Solution: The regression equation is

LVO−=1.74−0.233 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

Answer 30

Expert Solution

Answer 31

Expert Solution

Answer 32

Expert Solution

Answer 33

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−=1.74−0.233 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%.

Answer 34

To determine

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

Expert Solution

Answer to Problem 45E

Solution: The Regression equation is

LVO−=1.31−0.188 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−=1.31−0.188 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%.

Answer 35

To determine

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

Answer 36

Expert Solution

Answer to Problem 45E

Solution: The Regression equation is

LVO−=1.31−0.188 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

Answer 37

Expert Solution

Answer 38

Expert Solution

Answer 39

Expert Solution

Answer 40

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−=1.31−0.188 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%.

Answer 41

Ch. 11.1 - Prob. 1UYK Ch. 11.1 - Prob. 2UYK Ch. 11.1 - Prob. 3E Ch. 11.1 - Prob. 4E Ch. 11.1 - Prob. 5E Ch. 11.1 - Prob. 6E Ch. 11.1 - Prob. 7E Ch. 11.1 - Prob. 8E Ch. 11.1 - Prob. 9E Ch. 11.1 - Prob. 10E

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

Concept explainers

Videos

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

Answer to Problem 45E

Explanation of Solution

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

Answer to Problem 45E

Explanation of Solution

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

Answer to Problem 45E

Explanation of Solution

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

Answer to Problem 45E

Explanation of Solution

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

Answer to Problem 45E

Explanation of Solution

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Chapter 11 Solutions