QUANTITATIVE ANALYSIS FOR
MANAGEMENT,
14TH EDITION By RENDER
All Chapters 1 to15
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Copyright © 2024 Pearson Education, Inc.
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,TABLE OF CONTENT
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1. Introduction to Quantitative Analysisn n n
2. Probability Concepts and Applications
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3. Decision Analysisn
4. Regression Models n
5. Forecasting
6. Inventory Control Models
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7. Linear Programming Models: Graphical and Comput
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er Methods
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8. Linear Programming Applications
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9. Transportation, Assignment, and Network Models n n n n
10. Integer Programming, Goal Programming, and N
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onlinear Programming
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11. Project Management n
12. Waiting Lines and Queuing Theory Models
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13. Simulation Modeling n
14. Markov Analysis n
15. Statistical Quality Control n n
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Copyright © 2024 Pearson Education, Inc.
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,CHAPTER 1 n
Introduction to Quantitative Analysis n n n
TEACHING SUGGESTIONS n
Teaching Suggestion 1.1: Importance of Qualitative Factors.
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Section 1.1 gives students an overview of quantitative analysis. In this section, a number
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nof qualitative factors, including federal legislation and new technology, are discussed. Stud
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ents can be asked to discuss other qualitative factors that could have an impact on quantit
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ative analysis. Waiting lines and project planning can be used as examples.
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Teaching Suggestion 1.2: Discussing Other Quantitative Analysis Problems.
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Section 1.2 covers an application of the quantitative analysis approach. Students can be aske
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d to describe other problems or areas that could benefit from quantitative analysis.
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Teaching Suggestion 1.3: Discussing Conflicting Viewpoints.
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Possible problems in the QA approach are presented in this chapter. A discussion of conflict
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ing viewpoints within the organization can help students understand this problem. For exa
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mple, how many people should staff a registration desk at a university? Students will wa
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nt more staff to reduce waiting time, while university administrators will want less staf
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f to save money. A discussion of these types of conflicting viewpoints will help students
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nunderstand some of the problems of using quantitative analysis.
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Teaching Suggestion 1.4: Difficulty of Getting Input Data.
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A major problem in quantitative analysis is getting proper input data. Students can be aske
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d to explain how they would get the information they need to determine inventory or
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dering or carrying costs. Role- n n n n
playing with students assuming the parts of the analyst who needs inventory costs and the i
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nstructor playing the part of a veteran inventory manager can be fun and interesting. Stude
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nts quickly learn that getting good data can be the most difficult part of using quantitative
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analysis.
Teaching Suggestion 1.5: Dealing with Resistance to Change.
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, Resistance to change is discussed in this chapter. Students can be asked to explain how th
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ey would introduce a new system or change within the organization. People resisting ne
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w approaches can be a major stumbling block to the successful implementation of quan
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titative analysis. Students can be asked why some people may be afraid of a new invento
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ry control or forecasting system.
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SOLUTIONS TO DISCUSSION QUESTIONS AND PROBLEMS n n n n n
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1. Quantitative analysis involves the use of mathematical equations or relationships in an
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alyzing a particular problem. In most cases, the results of quantitative analysis will be one o
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r more numbers that can be used by managers and decision makers in making better deci
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sions. Calculating rates of return, financial ratios from a balance sheet and profit and loss
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statement, determining the number of units that must be produced in order to break even,
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and many similar techniques are examples of quantitative analysis. Qualitative analysis inv
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olves the investigation of factors in a decision-
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making problem that cannot be quantified or stated in mathematical terms. The state of
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nthe economy, current or pending legislation, perceptions about a potential client, and si
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milar situations reveal the use of qualitative analysis. In most decision-
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making problems, both quantitative and qualitative analysis are used. In this book, howev
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er, we emphasize the techniques and approaches of quantitative analysis.
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2. Quantitative analysis is the scientific approach to managerial decision making. This type o
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f analysis is a logical and rational approach to making decisions. Emotions, guesswork, and
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whim are not part of the quantitative analysis approach. A number of organizations suppo
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rt the use of the scientific approach: the Institute for Operation Research and Managem
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ent Science (INFORMS), Decision Sciences Institute, and Academy of Management.
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3. The three categories of business analytics are descriptive, predictive, and prescriptive.
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n Descriptive analytics provides an indication of how things were performed in the past. Pre
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dictive analytics uses past data to forecast what will happen in the future. Prescriptive an
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alytics uses optimization and other models to present better ways for a company to operate
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nto reach goals and objectives.
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1-4. Quantitative analysis is a step-by-
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step process that allows decision makers to investigate problems using quantitative tech
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niques. The steps of the quantitative analysis process include defining the problem, devel
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oping a model, acquiring input data, developing a solution, testing the solution, analyzin
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g the results, and implementing the results. In every case, the analysis begins with defini
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ng the problem. The problem could be too many stockouts, too many bad debts, or d
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etermining the products to produce that will result in the maximum profit for the organ
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ization. After the problems have been defined, the next step is to develop one or more
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n models. These models could be inventory control models, models that describe the debt sit
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uation in the organization, and so on. Once the models have been developed, the next ste
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