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Reading 12- LOS b: Q5- 6

5.You have been asked to forecast the level of operating profit for a proposed new branch of a tire store. This forecast is one component in forecasting operating profit for the entire company for the next fiscal year. You decide to conduct multiple regression analysis using "branch store operating profit" as the dependent variable and three independent variables. The three independent variables are "population within 5 miles of the branch," "operating hours per week," and "square footage of the facility." You used data on the company's existing 23 branches to develop the model (n=23).

 

Regression of Operating Profit on Population, Operating Hours, and Square Footage

Dependent Variable

Operating Profit (Y)

Independent Variables

Coefficient Estimate

t-value

Intercept

103,886

2.740

Population within 5 miles (X1)

4.372

2.133

Operating hours per week (X2)

214.856

0.258

Square footage of facility (X3)

56.767

2.643

 

 

 

R2

0.983

 

Adjusted R2

0.980

 

F-Statistic

360.404

 

Standard error of the model

19,181

 

 

 

Correlation Matrix

 

Y

X1

X2

X3

Y

1.00

 

 

 

X1

0.99

1.00

 

 

X2

0.69

0.67

1.00

 

X3

0.99

0.99

.71

1.00

 

Degrees of Freedom

.20

.10

.05

.02

.01

3

1.638

2.353

3.182

4.541

5.841

19

1.328

1.729

2.093

2.539

2.861

23

1.319

1.714

2.069

2.50

2.807

You want to evaluate the statistical significance of the slope coefficient of an independent variable used in this regression model. For 95 percent confidence, you should compare the t-statistic to the critical value from a t-table using:

A)   19 degrees of freedom and 0.05 level of significance for a two-tailed test.

B)   24 degrees of freedom and 0.05 level of significance for a one-tailed test.

C)   24 degrees of freedom and 0.05 level of significance for a two-tailed test.

D)   19 degrees of freedom and 0.05 level of significance for a one-tailed test.

 

6.The probability of finding a value of t for variable X1 that is as large or larger than |2.133| when the null hypothesis is true is:

A)   between 1% and 2%.

B)   between 5% and 10%.

C)   between 10% and 20%.

D)   between 2% and 5%.

 

5.You have been asked to forecast the level of operating profit for a proposed new branch of a tire store. This forecast is one component in forecasting operating profit for the entire company for the next fiscal year. You decide to conduct multiple regression analysis using "branch store operating profit" as the dependent variable and three independent variables. The three independent variables are "population within 5 miles of the branch," "operating hours per week," and "square footage of the facility." You used data on the company's existing 23 branches to develop the model (n=23).

 

Regression of Operating Profit on Population, Operating Hours, and Square Footage

Dependent Variable

Operating Profit (Y)

Independent Variables

Coefficient Estimate

t-value

Intercept

103,886

2.740

Population within 5 miles (X1)

4.372

2.133

Operating hours per week (X2)

214.856

0.258

Square footage of facility (X3)

56.767

2.643

 

 

 

R2

0.983

 

Adjusted R2

0.980

 

F-Statistic

360.404

 

Standard error of the model

19,181

 

 

 

Correlation Matrix

 

Y

X1

X2

X3

Y

1.00

 

 

 

X1

0.99

1.00

 

 

X2

0.69

0.67

1.00

 

X3

0.99

0.99

.71

1.00

 

Degrees of Freedom

.20

.10

.05

.02

.01

3

1.638

2.353

3.182

4.541

5.841

19

1.328

1.729

2.093

2.539

2.861

23

1.319

1.714

2.069

2.50

2.807

You want to evaluate the statistical significance of the slope coefficient of an independent variable used in this regression model. For 95 percent confidence, you should compare the t-statistic to the critical value from a t-table using:

A)   19 degrees of freedom and 0.05 level of significance for a two-tailed test.

B)   24 degrees of freedom and 0.05 level of significance for a one-tailed test.

C)   24 degrees of freedom and 0.05 level of significance for a two-tailed test.

D)   19 degrees of freedom and 0.05 level of significance for a one-tailed test.

 

6.The probability of finding a value of t for variable X1 that is as large or larger than |2.133| when the null hypothesis is true is:

A)   between 1% and 2%.

B)   between 5% and 10%.

C)   between 10% and 20%.

D)   between 2% and 5%.

 

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