Statistics Exam MUST BE GREAT IN STATISTICS/ MODELS MANGEMENT!!! Question 1 20 points 1. Show a separate graph of the constraint lines and the so

Statistics Exam
MUST BE GREAT IN STATISTICS/ MODELS MANGEMENT!!!

Question 1 20 points

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Statistics Exam MUST BE GREAT IN STATISTICS/ MODELS MANGEMENT!!! Question 1 20 points 1. Show a separate graph of the constraint lines and the so
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1. Show a separate graph of the constraint lines and the solutions that satisfy each of the following constraints:

a. 15X + 7Y 75

b. -5X + 15Y 150

c. 3Y 21

d. -4X 60

e. 5X + 3Y 0

Question 2 20 points

2. Consider the following linear program:

Maximize 32X + 15Y

s.t.

Constraint 1 5X + 20Y 120

Constraint 2 8X + 15Y 150

Constraint 3 3X – 6Y 30

X,Y 0

a. Show the graph and the feasible region

b. Shade the feasible region

c. Identify the optimal solution point on your graph

d. What are the values of X and Y at the optimal solution?

X Y

e. What is the optimal value of the objective function?

Question 3 20 points

3. Consider the following linear program. The cost per Dinner plate is $0.5 and the cost per Soup plate is $0.25:

Miniminze 18D + 12S

s.t.

Constraint 1 D 60

Constraint 2 S 36

Constraint 3 0.25D + 0.75S 70

Constraint 4 1.5D – 0.5S 120

D, S 0

Let D = Dinner plate

Let S = Soup plate

a. Insert a graph to show each constraint and the feasible region.

b. Shade the feasible region.

c. Identify the optimal solution point on the graph.

d. What is the optimal value of the objective function?

e. What is the optimal value of the objective function (dollar value)?

f. What is the optimal value for Dinner plates?

D

g. What is the optimal values for Soup plates?

S

h. How much would cost to make the optimal values of Dinner plates (dollar value)?

i. How much would cost to make the optimal values of Soup plates (dollar value)?

j. Which constraints are binding?

Question 4 20 points

4. By using solver, answer the following questions based on the the following LP model:

Maximize 70A + 50B

s.t.

Constraint 1 12A + 13B 1000

Constraint 2 15B 900

Constraint 3 12A – 20B 800

Constraint 4 15A 850

A, B 0

a. Insert the sensitivity and limit reports.

b.What is the optimal objective value of the objective function?

c. What are the optimal values of the two decision variables?

A B

d. What are the ranges optimality?

e. What are the range of feasibility for each constraint?

f. What are the dual values for each constraint?

g. Would it be beneficial to increase the maximum value of constraint 1 to 1200? Explain.

h. What would happen to constraint 2 if we decrease the final value to 400?

i. What would happen if we would change the RHS of constraint 3 to 650? Explain.

j. What would happen if we would change the RHS of constratint 4 to 860? Explain.

Question 5 20 points

5. The solver solution of the problem is shown on the side:

a. What is the optimal solution?

b. What is the value of objective function?

c. Which constraints are binding? Interpret each.

d. Specifiy the objective function ranges.

e. Identify each of the right-hand-side ranges.

f. Suppose that the variable Pasta decreases from its current value to 3. How does the optimal solution change, if at all?

g. Suppose that variable Salad increases from its current value to 10. How does the optimal solution change, if at all?

h. Would be beneficial to increase the maximum amount shown in constraint 2 to 20? Why or why not, and what would happen to the objective function?

*Shadow Price= Dual Value

i. Would be beneficial to increase the amount shown in constraint 1 to 30? Why or why not, and what would happen to optimal solution?

j. If the available value of constraint 3 is increased by 50, will the dual value of the constraint change? Explain.

Extra Credit – 10 points

Car Weight (in lbs) Car MPG

3250 28

3675 23

3840 19

3935 20

2140 43

4010 22

2565 34

3450 22

2900 28

3345 25

3545 24

3050 31

2540 34

2410 36

2865 30

3810 22

The values above on column A list the weight in pounds of 16 different cars made in 2020. The values in Column B are the corresponding gas mileages for each car.

Insert a linear programming graph with the regression model and R-squared value.

a. What is the regression model/equation?

b. What is the R-squared value?

c. What does the graph tell us about the general relationship between these two variables?

d. I am planning to purchase a relatively new (2020) car but I am concerned about getting good gas mileage.

Using this regression equation, tell me friend the expected gas mileage at 2750 pounds.

e. The value found on the question above sounds high. What would you tell me based on all the information found to justify your response?