Statistics Exam
Question 1 20 points
| 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? | |