1.
The following is a payoff table giving profits for various situations.

State

Of

Nature

Alternatives

A

B

C

Alternative 1

100

120

180

Alternative 2

120

140

120

Alternative 3

200

100

50

Do Nothing

0

0

0

The probabilities for states of
nature A, B, and C are 0.3, 0.5, and 0.2, respectively. What decision
should be made based on the minimax regret criterion?

(Points : 2.5)

Alternative 1
Alternative 2
Alternative 3
Do Nothing
None of the above
Question 3.
3.
The following is a payoff table giving profits for various situations.

State

Of

Nature

Alternatives

A

B

C

Alternative 1

100

120

180

Alternative 2

120

140

120

Alternative 3

200

100

50

Do Nothing

0

0

0

The probabilities for states of
nature A, B, and C are 0.3, 0.5, and 0.2, respectively. What decision
should be made based on the equally likely criterion?

(Points : 2.5)

Alternative 1
Alternative 2
Alternative 3
Do Nothing
None of the above

Question 12.
12.
A store of Pizza Hut
provides the following data on the quantity of pizzas sold during the
month of January through July 2014, the price of a large pizza, and the
advertising expenses.

Quantity Sold

Price

Advertising Expenses

8500

$10

$3,000

4800

14

1000

6500

12

1500

7800

11

2000

6000

13

1500

8000

10

2500

7000

11

1800

The regression output is as follow:

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.98154

R Square

0.96342

Adjusted R Square

0.94513

Standard Error

301.7577

Observations

7

ANOVA

df

SS

MS

F

Significance F

Regression

2

9592912

4796456

52.67491

0.001338

Residual

4

364230.8

91057.69

Total

6

9957143

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Intercept

12460.58

3181.967

3.915998

0.017306

3626.02

21295.13

Price

-577.885

204.148

-2.83071

0.047311

-1144.69

-11.0789

Advertising Expenses

0.615385

0.458403

1.342454

0.250575

-0.65735

1.888115

Which of the following is correct about the relationship between quantity sold and the price of pizza?
(Points : 2.5)

There
is a positive relationhsip between quantity sold and price of pizza and
the relationship is statistically significant at 1%.
There
is a negative relationship between the quantity sold and the price of
pizza and the relationship is statistically significant at 5%.
There
is a negative relationship between quantity sold and the price of pizza
but the relationship is not statistically significant.
There is insufficient information to answer the question.

None of the above.

Question 23.
23.
A store of Pizza Hut
provides the following data on the quantity of pizzas sold during the
month of January through July 2014, the price of a large pizza, and the
advertising expenses.

Quantity Sold

Price

Advertising Expenses

8500

$10

$3,000

4800

14

1000

6500

12

1500

7800

11

2000

6000

13

1500

8000

10

2500

7000

11

1800

The regression output is as follow:

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.98154

R Square

0.96342

Adjusted R Square

0.94513

Standard Error

301.7577

Observations

7

ANOVA

df

SS

MS

F

Significance F

Regression

2

9592912

4796456

52.67491

0.001338

Residual

4

364230.8

91057.69

Total

6

9957143

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Intercept

12460.58

3181.967

3.915998

0.017306

3626.02

21295.13

Price

-577.885

204.148

-2.83071

0.047311

-1144.69

-11.0789

Advertising Expenses

0.615385

0.458403

1.342454

0.250575

-0.65735

1.888115

What is the coefficient of determination?

(Points : 2.5)

0.98154
0.96342
0.94513
0.615385
None of the above

Question 24.
24.
The following is a payoff table giving profits for various situations.

State

Of

Nature

Alternatives

A

B

C

Alternative 1

100

120

180

Alternative 2

120

140

120

Alternative 3

200

100

50

Do Nothing

0

0

0

The probabilities for states of nature A, B, and C are 0.3, 0.5, and 0.2, respectively. What decision would a pessimist make?

(Points : 2.5)

Alternative 1
Alternative 2
Alternative 3
Do Nothing
None of the above

Question 27.
27.
The following is a payoff table giving profits for various situations.

State

Of

Nature

Alternatives

A

B

C

Alternative 1

100

120

180

Alternative 2

120

140

120

Alternative 3

200

100

50

Do Nothing

0

0

0

The probabilities for states of nature A, B, and C are 0.3, 0.5, and 0.2, respectively. What decision would an optimist make?

(Points : 2.5)

Alternative 1
Alternative 2
Alternative 3
Do Nothing
State of Nature A

Question 32.
32.
A store of Pizza Hut
provides the following data on the quantity of pizzas sold during the
month of January through July 2014, the price of a large pizza, and the
advertising expenses.

Quantity Sold

Price

Advertising Expenses

8500

$10

$3,000

4800

14

1000

6500

12

1500

7800

11

2000

6000

13

1500

8000

10

2500

7000

11

1800

The regression output is as follow:

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.98154

R Square

0.96342

Adjusted R Square

0.94513

Standard Error

301.7577

Observations

7

ANOVA

df

SS

MS

F

Significance F

Regression

2

9592912

4796456

52.67491

0.001338

Residual

4

364230.8

91057.69

Total

6

9957143

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Intercept

12460.58

3181.967

3.915998

0.017306

3626.02

21295.13

Price

-577.885

204.148

-2.83071

0.047311

-1144.69

-11.0789

Advertising Expenses

0.615385

0.458403

1.342454

0.250575

-0.65735

1.888115

What is the correlation coefficient?

(Points : 2.5)

0.96342
0.615385
0.98154
0.94513
None of the above

Question 34.
34.
A store of Pizza Hut
provides the following data on the quantity of pizzas sold during the
month of January through July 2014, the price of a large pizza, and the
advertising expenses.

Quantity Sold

Price

Advertising Expenses

8500

$10

$3,000

4800

14

1000

6500

12

1500

7800

11

2000

6000

13

1500

8000

10

2500

7000

11

1800

The regression output is as follow:

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.98154

R Square

0.96342

Adjusted R Square

0.94513

Standard Error

301.7577

Observations

7

ANOVA

df

SS

MS

F

Significance F

Regression

2

9592912

4796456

52.67491

0.001338

Residual

4

364230.8

91057.69

Total

6

9957143

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Intercept

12460.58

3181.967

3.915998

0.017306

3626.02

21295.13

Price

-577.885

204.148

-2.83071

0.047311

-1144.69

-11.0789

Advertising Expenses

0.615385

0.458403

1.342454

0.250575

-0.65735

1.888115

Which of the two independent variables, Price and advertising expenses, is a good predictor of quantity sold?

(Points : 2.5)

Price only
Advertising Expenses only
Both Price and Advertising Expenses
Neither
None of the above

Question 35.
35.
A store of Pizza Hut
provides the following data on the quantity of pizzas sold during the
month of January through July 2014, the price of a large pizza, and the
advertising expenses.

Quantity Sold

Price

Advertising Expenses

8500

$10

$3,000

4800

14

1000

6500

12

1500

7800

11

2000

6000

13

1500

8000

10

2500

7000

11

1800

The regression output is as follow:

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.98154

R Square

0.96342

Adjusted R Square

0.94513

Standard Error

301.7577

Observations

7

ANOVA

df

SS

MS

F

Significance F

Regression

2

9592912

4796456

52.67491

0.001338

Residual

4

364230.8

91057.69

Total

6

9957143

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Intercept

12460.58

3181.967

3.915998

0.017306

3626.02

21295.13

Price

-577.885

204.148

-2.83071

0.047311

-1144.69

-11.0789

Advertising Expenses

0.615385

0.458403

1.342454

0.250575

-0.65735

1.888115

Which of the following is correct about the regression model?

(Points : 2.5)

The model is not a good prediction model.

The low significance level of F suggests that the model is not good.

Since significance F is less than 1%, it can be concluded that the model is good prediction model.
The model is not good because the coefficient of determination is near 0.
None of the above

Question 44.
44.
One problem in using a quantitative model is that the necessary data may be unavailable.

(Points : 2.5)

True
False
## Solution: Saint GBA334 midterm exam

Tutorial # 00032278Posted By: echo7 Posted on: 11/22/2014 09:15 PM