Solution Manual for An Introduction to Management Science 15th Edition by Anderson
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By: Anderson
Edition: 15th Edition
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Solution Manual for An Introduction to Management Science 15th Edition by Anderson
Chapter 1
Introduction
Learning Objectives
- Develop a general understanding of the management science/operations research approach to decision making.
- Realize that quantitative applications begin with a problem situation.
- Obtain a brief introduction to quantitative techniques and their frequency of use in practice.
- Understand that managerial problem situations have both quantitative and qualitative considerations that are important in the decision making process.
- Learn about models in terms of what they are and why they are useful (the emphasis is on mathematical models).
- Identify the step-by-step procedure that is used in most quantitative approaches to decision making.
- Learn about basic models of cost, revenue, and profit and be able to compute the breakeven point.
- Obtain an introduction to the use of computer software packages such as Microsoft Excel in applying quantitative methods to decision making.
- Understand the following terms:
model infeasible solution
objective function management science
constraint operations research
deterministic model fixed cost
stochastic model variable cost
feasible solution breakeven point
Solutions:
- Management science and operations research, terms used almost interchangeably, are broad disciplines that employ scientific methodology in managerial decision making or problem solving. Drawing upon a variety of disciplines (behavioral, mathematical, etc.), management science and operations research combine quantitative and qualitative considerations in order to establish policies and decisions that are in the best interest of the organization.
- Define the problem
Identify the alternatives
Determine the criteria
Evaluate the alternatives
Choose an alternative
For further discussion see section 1.3
- See section 1.2.
- A quantitative approach should be considered because the problem is large, complex, important, new and repetitive.
- Models usually have time, cost, and risk advantages over experimenting with actual situations.
- Model (a) may be quicker to formulate, easier to solve, and/or more easily understood.
- Let d = distance
m = miles per gallon
c = cost per gallon,
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Description | By: Anderson Edition: 15th Edition Format: Downloadable ZIP Fille Resource Type: Solution manual Duration: Unlimited downloads Delivery: Instant Download | By: Stevenson Edition: 13th Edition Format: Downloadable ZIP Fille Resource Type: Solution Manual Duration: Unlimited downloads Delivery: Instant Download | By: Stevenson Edition: 6th Edition Format: Downloadable ZIP Fille Resource Type: Solution manual Duration: Unlimited downloads Delivery: Instant Download | By: Wisner Edition: 5th Edition Format: Downloadable ZIP Fille Resource Type: Solution manual Duration: Unlimited downloads Delivery: Instant Download | By: Winston Edition: 6th Edition Format: Downloadable ZIP Fille Resource Type: Solution manual Duration: Unlimited downloads Delivery: Instant Download | Edition: 11th Edition Format: Downloadable ZIP Fille Resource Type: Solution manual Duration: Unlimited downloads Delivery: Instant Download | ||
Content | Solution Manual for An Introduction to Management Science 15th Edition by AndersonChapter 1 Introduction Learning Objectives
| Solution Manual for Operations Management 13th Edition by Stevensonchapter 19 Linear Programming Teaching Notes The main goal of this supplement is to provide students with an overview of the types of problems that have been solved using linear programming (LP). In the process of learning the different types of problems that can be solved with LP, students also must develop a very basic understanding of the assumptions and special features of LP problems of management test bank. Students also should learn the basics of developing and formulating linear programming models for simple problems, solve two-variable linear programming problems by the graphical procedure, and interpret the resulting outcome. In the process of solving these graphical problems, we must stress the role and importance of extreme points in obtaining an optimal solution. Improvements in computer hardware and software technology and the popularity of the software package Microsoft Excel make the use of computers in solving linear programming problems accessible to many users. Therefore, a main goal of the chapter should be to allow students to solve linear programming problems using Excel. More importantly, we need to ensure that students are able to interpret the results obtained from Excel or any another computer software package. Answers to Discussion and Review Questions
| Solution Manual for Operations Management 6th CANADIAN Edition by StevensonChapter No 1 INTRODUCTION TO Operations Management Teaching Notes The initial meeting with the class (the first chapter) is primarily to overview the course (and textbook), and to introduce the instructor and his/her interest in Operations Management (OM). The course outline (syllabus), the objectives of the course and topics, chapters, and pages of text covered in the course, as well as problems/mini-cases, to be done in class, videos to watch, Excel worksheets to use, etc. are announced to the class. Many students may know little about OM and the types of jobs available. This point can be addressed in order to generate enthusiasm for the course. The Learning Objectives at the beginning of the chapter indicate the highlights of the chapter. Answers to Discussion and Review Questions
| Solution Manual for Principles of Supply Chain Management 5th Edition by WisnerPRINCIPLES OF SUPPLY CHAIN MANAGEMENT: A BALANCED APPROACH, 5thEd. Answers to Questions/Problems Chapter OneDiscussion Questions
| Solution Manual for Practical Management Science 6th Edition by Winston
| Solution Manual for Statistics for Management and Economics 11th Edition by KellerChapter 11.2 Statistics for Management and Economics Descriptive techniques summarize data. Inferential techniques draw inferences about a population based on sample data. 1.3 Statistics for Management and Economics a The population is the 25,000 registered voters. b The sample is the 200 registered voters. cThe 48% figure is the statistic 1.4 Statistics for Management and Economics a The population is the complete production run. b The sample is comprised of the 1,000 chips. c The parameter is the proportion of defective chips in the production run. d The statistic is the proportion of defective chips in the sample. e The 10% figure refers to the parameter. fThe 7.5% figure refers to the statistic. g We can estimate the population proportion is 7.5%. Statistical inference methods will allow us to determine whether we have enough statistical evidence to reject the claim.as the sample proportion. 1.5 Statistics for Management and Economics Draw a random sample from the population of graduates who have majored in your subject and a random sample of graduates of other majors and record their highest salary offers. 1.6 Statistics for Management and Economics a Flip the coin (say 100 times) and record the number of heads (assuming that you are interested in the number of heads). b The population is composed of the theoretical result of flipping the coin an infinite number of times and recording either “heads” or “tails”. cThe sample is comprised of the “heads” and “tails” in the sample. d The parameter is the proportion of heads (again assuming that your interest is the number of heads rather than tails) in the population. e The statistic is the proportion of heads (or tails depending on the choice made in part d). fThe sample statistic can be used to judge whether the coin is actually fair. 1.7 a We would conclude that the coin is not fair. b We may conclude that there is some evidence that the coin is not fair. 1.8 aThe population is made up of the propane mileage of all the cars in the fleet. b The parameter is the mean propane mileage of all the cars in the fleet. c The sample is composed of the propane mileage of the 50 cars. d The statistic is the mean propane mileage of the 50 cars in the sample. e We can use the sample statistic to estimate the population parameter. | ||
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