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This Question: 1 pt 13 of 15 (0 complete) This Test: 15 pts possible A coffee co

ID: 3294961 • Letter: T

Question

This Question: 1 pt 13 of 15 (0 complete) This Test: 15 pts possible A coffee company uses a data-based approach to improving the quality and customer satisfaction of its products When survey data indicated that the coffee company needed to improve its package-sealing process, an experiment was conducted to determine the factors in the bag-sealing equipment that might be affecting the ease of opening the bag without tearing the inner liner of the bag. One factor that could affect the rating of the ability of the bag to resist tears was the plate gap on the bag-sealing equipment. Data were collected on 19 bags in which the plate gap was varied. Complete parts (a) through (e) below Click the icon to view the data table a. Construct a scatter plot. Choose the correct graph below Tear Rating Plate Gap Tear Rating Plate Gap b. Assuming a linear relationship, use the least-squares method to find the regression coefficients bo and b.

Explanation / Answer

Question a)

Answer: Option B

Question b)

We copy the data in excel. There we go to Data Analysis and select the Regression. We input the data for x and y and we get the regression output where we can find the b0 and b1 values.

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.549481

R Square

0.301929

Adjusted R Square

0.260866

Standard Error

1.09878

Observations

19

ANOVA

df

SS

MS

F

Significance F

Regression

1

8.8772

8.8772

7.3528

0.0148

Residual

17

20.5244

1.2073

Total

18

29.4016

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Intercept

1.0481

0.2696

3.8879

0.0012

0.4793

1.6169

X Variable 1

2.0100

0.7413

2.7116

0.0148

0.4461

3.5740

Answer:

bo= 1.0481

b1 = 2.0100

Question c)

Answer: Option A

Question d)

Answer: 1.0481

Question e)

Answer: Option B

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.549481

R Square

0.301929

Adjusted R Square

0.260866

Standard Error

1.09878

Observations

19

ANOVA

df

SS

MS

F

Significance F

Regression

1

8.8772

8.8772

7.3528

0.0148

Residual

17

20.5244

1.2073

Total

18

29.4016

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Intercept

1.0481

0.2696

3.8879

0.0012

0.4793

1.6169

X Variable 1

2.0100

0.7413

2.7116

0.0148

0.4461

3.5740

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