Business

Intended for courses in Management Science or Quantitative Methods.

This best-selling text has long been considered one of the most student accessible texts for the management science course. The new edition retains and updates the traditional, comprehensive coverage of past editions but “fine tunes” the coverage and adds many new examples and exercises.

Intended for courses in Management Science or Quantitative Methods.

This best-selling text has long been considered one of the most student accessible texts for the management science course. The new edition retains and updates the traditional, comprehensive coverage of past editions but “fine tunes” the coverage and adds many new examples and exercises.

How do you motivate the chapter material?  What types of elements do you look for to drive the concepts home for students? 

Rich Real-world Applications

• Modeling in the Real World boxes
  • Demonstrate the application of the quantitative analysis approach to every technique discussed in the book.
• Procedure boxes
  • Summarize the more complex quantitative techniques, presenting them as a series of easily understandable steps.
• Margin notes
  • Highlight the important topics in the text.
• History boxes
  • Provide interesting asides related to the development of techniques and the people who originated them.
• QA in Action boxes
  • Summarize published articles illustrating how real organizations have used quantitative analysis to solve problems.

What type of problems do you assign? What resources help students review the concepts?

• Solved Problems
  • Serve as models for students in solving their own homework problems.
• Discussion Questions
  • Test student’s understanding of the concepts and definitions.
• Homework Problems are applications-oriented and test the student’s ability to solve exam-type problems. T
  • Provide problems that progress in level of difficulty: introductory (one bullet), moderate (two bullets), and challenging (three bullets).
• Internet Homework Problems
  • Provide additional problems for students to work on the companion Web site.
• Self Tests
  • Allow students to test their knowledge of important terms and concepts in preparation for quizzes and examinations.
• Case Studies
  •  Provide additional challenging managerial applications.
• Glossaries
  • Define important terms.

What type of software do you use to help students problem-solve?

Excel. For students already familiar with Excel, instructions and screen captures are provided to highlight functions and tools that are directly related to quantitative analysis. New appendices provide succinct instructions and examples in several chapters. Excel is used for computations with the normal distribution, the binomial distribution, Bayes’ theorem, simple and multiple regression, the analytic hierarchy process, Markov analysis, matrix operations, and other models. From the previous edition, Excel is also used for linear and nonlinear programming, simulation, and forecasting.

Excel QM. Excel QM is an Excel add-in that makes the use of Excel even easier. It is used to solve many of the problems and examples found in the text. The use of Excel QM is integrated into most chapters.

 

QM for Windows. QM for Windows, developed by Professor Howard Weiss, has long been a preferred software package for quantitative techniques.  It is menu-driven and very easy-to-use so that students with limited computer experience find it very user friendly. The full version of this software is on the Student CD-ROM and updates to this valuable  package are available to the student at www.prenhall.com/weiss. 

 

This text is available for personalization in the PHCBR custom database program.  Select only the chapters you require or supplement with recommended case studies all under one cover.  CLICK HERE to go directly to the PHCBR book-build site or visit our product page for additional information at pearsoncustom.com/business.

Cohesive Treatment of Decision Models

All models for decision theory have been combined into one chapter.  Decision trees and utility theory are now presented along with decision tables.

New Chapter on Regression Analysis

This includes simple linear regression, multiple regression, and a brief discussion of nonlinear regression.  Statistical inference on the overall model is presented.  Other topics include dummy or indicator variables, model building, and cautions and pitfalls of using regression analysis.

Expanded Coverage of Forecasting

The forecasting chapter has been expanded to include the additive approach to decomposition.  Dummy variables are used in regression models to incorporate seasonal variations into the forecasts.

Enhanced Inventory Chapter

Now includes just-in-time (JIT), materials requirements planning (MRP), and enterprise resource planning (ERP) to provide a more complete introduction to inventory models in one chapter.

CD-ROM MODULES

To streamline the book, six topics are contained in modules available on the student CD-ROM included with the book. The six modules are:

• Analytic Hierarchy Process
• Dynamic Programming
• Decision Theory and the Normal Distribution
• Game Theory
• Mathematical Tools: Matrices and Determinants
• Calculus-Based Optimization

1. Introduction to Quantitative Analysis

     Introduction. What Is Quantitative Analysis? The Quantitative Analysis Approach. How to Develop a Quantitative Analysis Model.
     The Role of Computers and Spreadsheet Models in the Quantitative Analysis Approach. Possible Problems in the Quantitative Analysis
     Approach. Implementation—Not Just the Final Step 
       

2. Probability Concepts and Applications

     Introduction. Fundamental Concepts. Mutually Exclusive and Collectively Exhaustive Events. Statistically Independent Events. 
     Statistically Dependent Events. Revising Probabilities with Bayes’ Theorem. Further Probability Revisions. Random Variables. 
     Probability Distributions. The Binomial Distribution. The Normal Distribution. The Exponential Distribution.  The Poisson Distribution.

 
3. Decision Models and Decision Trees

     Introduction. The Six Steps in Decision Making. Types of Decision-Making Environments. Decision Making under Uncertainty. 
     Decision Making under Risk. Decision Trees. How Probability Values Are Estimated by Bayesian Analysis.  Utility Theory. 

4. Regression Models
   
     Introduction. Scatter Diagrams. Simple Linear Regression. Measuring the Fit of the Regression Model. Assumptions of the Regression
     Model. Testing the Model for Significance. Multiple Regression Analysis.  Binary or Dummy Variables. Model Building. Nonlinear 
     Regression. Cautions and Pitfalls in Regression Analysis.

5. Forecasting 
   
     Introduction. Types of Forecasts. Scatter Diagrams and Time Series. Measures of Forecast Accuracy. Time-Series Forecasting Models. 
     Monitoring and Controlling Forecasts. Using the Computer to Forecast.

6. Inventory Control Models 
   
     Introduction. Importance of Inventory Control. Inventory Decisions. Economic Order Quantity: Determining How Much to Order
     Reorder Point: Determining When to Order. EOQ Without the Instantaneous Receipt Assumption. Quantity Discount Models.
     Use of Safety Stock. ABC Analysis. Dependent Demand: The Case for Materials Requirements Planning. Just-In-Time Inventory Control.
     Enterprise Resource Planning.

7. Linear Programming Models: Graphical and Computer Methods

     Introduction. Requirements of a Linear Programming Problem. Formulating LP Problems. Graphical Solution to a LP Problem. Solving Flair 
     Furniture’s LP Problem Using QM for Windows and Excel. Solving Minimization Problems. Four Special Cases in LP. Sensitivity Analysis. 

8. Linear Programming Modeling Applications and Computer Analyses 
   
     Introduction. Marketing Applications. Manufacturing Applications. Employee Scheduling Applications. Financial Applications. Transportation 
     Applications. Transshipment Applications. Ingredient Blending Applications.

9. Linear Programming: The Simplex Method

     Introduction. How to Set Up the Initial Simplex Solution. Simplex Solution Procedures. The Second Simplex Tableau Developing the Third 
     Tableau. Review of Procedures for Solving LP Maximization Problems. Surplus and Artificial Variables Solving Minimization Problems. 
     Review of Procedures for Solving LP Minimization Problems. Special Cases.Sensitivity Analysis with the Simplex Tableau. The Dual.  
     Karmarkar’s Algorithm.
 
    

10. Transportation and Assignment Models

        Introduction. Setting Up a Transportation Problem. Developing an Initial Solution: Northwest Corner Rule. Stepping-Stone Method: 
        Finding a Least-Cost Solution.  MODI Method. Vogel’s Approximation Method: Another Way to  Find an Initial Solution.  Unbalanced 
        Transportation Problems. Degeneracy in Transportation Problems.  More Than One Optimal Solution. Unacceptable or Unacceptable or 
        Prohibited Routes. Facility Location Analysis. Approach of the Assignment Model. Unbalanced Assignment Problems. Maximization 
        Assignment Problems

11. Integer Programming, Goal Programming, and Nonlinear Programming

       Introduction. Integer Programming. Modeling with 0–1 Variables. Goal Programming. Nonlinear Programming. 
 
  

12. Network Models 
    
       Introduction. Minimal-Spanning Tree Technique. Maximal-Flow Technique. Shortest-Route Technique.
 
      

13. Project Management

       Introduction. PERT. PERT/Cost. Critical Path Method. Other Topics in Project Management.

14. Waiting Lines and Queuing Theory Models

       Introduction. Waiting Line Costs. Characteristics of a Queuing System. Single-Channel Queuing Model with Poisson Arrivals and 
       Exponential Service Times (M/M/1). Multiple-Channel Queuing Model with Poisson Arrivals and Exponential Service Times (M/M/m). 
       Constant Service Time Model (M/D/1). Finite Population Model  (M/M/1 with Finite Source). Some General Operating Characteristic 
       Relationships. More Complex Queuing Models and  the Use of Simulation

15. Simulation Modeling

       Introduction. Advantages and Disadvantages of Simulation. Monte Carlo Simulation. Simulation and Inventory Analysis. Simulation of a 
       Queuing Problem. Fixed Time Increment and Next Event Increment Simulation Models. Simulation Model for a Maintenance Policy.
       Two Other Types of Simulation Models. Verification and Validation. Role of Computers in Simulation.
  
      

16. Markov Analysis

       Introduction. States and State Probabilities. Matrix of Transition Probabilities. Predicting Future Market Shares. Markov Analysis 
       of Machine Operations. Equilibrium Conditions. Absorbing States and the Fundamental Matrix: Accounts Receivable Application.

17. Statistical Quality Control

       Introduction. Defining Quality and TQM. Statistical Process Control. Control Charts for Variables. Control Charts for Attributes.
      
       

Appendices 
   

CD-ROM Modules

Management Science/Decision Modeling  [COMPREHENSIVE TEXTS]   (Decision Science)
Decision Science Software  (Decision Science)

• 
  Quantitative Analysis for Management, 10/E
  Render, Stair & Hanna
  ©2009 | Prentice Hall | Cloth Bound w/CD-ROM; 768 pp | Instock
  ISBN-10: 0136036252 | ISBN-13: 9780136036258
  Brief Description | Buy from myPearsonStore

  

  For courses in Management Science or Decision Modeling.

   

  Render/Stair/Hanna puts an emphasis on model building and computer applications to show students how the techniques presented in the book are used in business.

Companion Website - Render, 9/E
Render
©2006 | Prentice Hall | On-line Supplement | Instock
ISBN-10: 0131851977 | ISBN-13: 9780131851979

Review Copy and Student CD Package, 9/E
Render, Stair & Hanna
©2006 | Prentice Hall | Paper | Instock
ISBN-10: 0131544284 | ISBN-13: 9780131544284

Companion Website - Render, 9/E
Render
©2006 | Prentice Hall | On-line Supplement | Instock
ISBN-10: 0131851977 | ISBN-13: 9780131851979

Instructors Resource Center, 9/E
Render
©2006 | Prentice Hall | On-line Supplement | Instock
ISBN-10: 0131851942 | ISBN-13: 9780131851948
  View Downloadable Files

Companion Website - Render, 9/E
Render
©2006 | Prentice Hall | On-line Supplement | Instock
ISBN-10: 0131851977 | ISBN-13: 9780131851979

Production and Operations Management JIT
Simpson
©1993 | Prentice Hall | Paper | Estimated Availability : 12/31/9999
ISBN-10: 0205148506 | ISBN-13: 9780205148509

Companion Website - Render, 9/E
Render
©2006 | Prentice Hall | On-line Supplement | Instock
ISBN-10: 0131851977 | ISBN-13: 9780131851979

This package contains:
•   Render, Stair & Hanna, Quantitative Analysis for Management, 9/E (2006)
•   Render, Stair, Hanna & Weiss, Student CD, 9/E (2006)

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