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Question # 00714938 Posted By: spqr Updated on: 01/26/2019 08:07 PM Due on: 01/29/2019
Subject Statistics Topic Data Analysis Tutorials:
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Semester’s Chapters Assignments


Chapter 1



Chapter 11





Chapter 12




Chapter 15







Chapter 13

Chapter 13, problem


 8.  The ticket booth on the Tech campus is operated by one person, who is selling tickets for the annual Tech versus State football game on Saturday. The ticket seller can serve an average of 12 customers per hour; on average, 10 customers arrive to purchase tickets each hour (Poisson distributed). Determine the average time a ticket buyer must wait and the portion of time the ticket seller is busy.


10. The Dynaco Manufacturing Company produces a particular product in an assembly line opera- tion. One of the machines on the line is a drill press that has a single assembly line feeding into it. A partially completed unit arrives at the press to be worked on every 7.5 minutes, on aver- age. The machine operator can process an average of 10 parts per hour. Determine the average number of parts waiting to be worked on, the percentage of time the operator is working, and the percentage of time the machine is idle.


Chapter 16,

Problem 2


2.  Hayes Electronics in Problem 1 assumed with certainty that the ordering cost is $450 per order and the inventory carrying cost is $170 per unit per year. However, the inventory model param- eters are frequently only estimates that are subject to some degree of uncertainty. Consider four cases of variation in the model parameters: (a) Both ordering cost and carrying cost are 10% less than originally estimated, (b) both ordering cost and carrying cost are 10% higher than originally estimated, (c) ordering cost is 10% higher and carrying cost is 10% lower than originally esti- mated, and (d) ordering cost is 10% lower and carrying cost is 10% higher than originally esti- mated. Determine the optimal order quantity and total inventory cost for each of the four cases. Prepare a table with values from all four cases and compare the sensitivity of the model solution to changes in parameter values.












Chapter 8







Chapter 2 -4

The Kalo Fertilizer Company makes a fertilizer using two chemicals that provide nitrogen, phosphate, and potassium. A pound of ingredient 1 contributes 10 ounces of nitrogen and 6 ounces of phosphate, while a pound of ingredient 2 contributes 2 ounces of nitrogen, 6 ounces of phosphate, and 1 ounce of potassium. Ingredient 1 costs $3 per pound, and ingredient 2 costs $5 per pound. The company wants to know how many pounds of each chemical ingredient to put into a bag of fertilizer to meet the minimum requirements of 20 ounces of nitrogen, 36 ounces of phosphate, and 2 ounces of potassium while minimizing cost. 

Chapter 2 -5

The Pinewood Furniture Company produces chairs and tables from two resources—labor and wood. The company has 80 hours of labor and 36 board-ft. of wood available each day. Demand for chairs is limited to 6 per day. Each chair requires 8 hours of labor and 2 board-ft. of wood, whereas a table requires 10 hours of labor and 6 board-ft. of wood. The profit derived from each chair is $400 and from each table, $100. The company wants to determine the number of chairs and tables to produce each day in order to maximize profit.

Chapter 2 – 10

The Elixer Drug Company produces a drug from two ingredients. Each ingredient contains the same three antibiotics, in different proportions. One gram of ingredient 1 contributes 3 units, and 1 gram of ingredient 2 contributes 1 unit of antibiotic 1; the drug requires 6 units. At least 4 units of antibiotic 2 are required, and the ingredients contribute 1 unit each per gram. At least 12 units of antibiotic 3 are required; a gram of ingredient 1 contributes 2 units, and a gram of ingredi- ent 2 contributes 6 units. The cost for a gram of ingredient 1 is $80, and the cost for a gram of ingredient 2 is $50. The company wants to formulate a linear programming model to determine the number of grams of each ingredient that must go into the drug in order to meet the antibiotic requirements at the minimum cost.

  1. Formulate a linear programming model for this problem.
  2. Solve this model by using graphical analysis.


Chapter 3 – 22

The manager of a Burger Doodle franchise wants to determine how many sausage biscuits and ham biscuits to prepare each morning for breakfast customers. The two types of biscuits require the following resources: The franchise has 6 hours of labor available each morning. The manager has a contract with a local grocer for 30 pounds of sausage and 30 pounds of ham each morning. The manager also purchases 16 pounds of flour. The profit for a sausage biscuit is $0.60; the profit for a ham biscuit is $0.50. The manager wants to know the number of each type of biscuit to prepare each morning in order to maximize profit. Formulate a linear programming model for this problem.

Chapter 3 – 24

Solve the linear programming model developed in Problem 22 for the Burger Doodle restaurant by using the computer.

  1. Identify and explain the shadow prices for each of the resource constraints.

The sensitivity report shows the shadow prices. Shadow price is the increase in optimal value with per unit increase of a constraint. Labor and Ham both have a 0 value, meaning changing them would not change the optimal value. Sausage has a shadow of 1, meaning for every 1 unit of sausage increase profit would also increase by $1, but allowable increase/decrease for sausage is 10 and 4.29.  The flour also could increase total profit by 16 (it's shadow price) but has a restriction of 1 and 4 lbs up and down as well.

  1. Which of the resources constraints profit the most?

The flour profits the most with the highest shadow value.

  1. Identify the sensitivity ranges for the profit of a sausage biscuit and the amount of sausage available.

The allowable range for profit of a sauasge biscuit is between infinity and .5



Chapter 4







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