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Testbank for Quantitative Analysis for Management: (12th Edition) by Barry Render

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  • ISBN-10:  133507335 / ISBN-13:  9780133507331
  • Ebook Details

    • Edition: 12th Edition
    • Format: Downloadable ZIP Fille
    • Resource Type : Testbank
    • Publication: 2014
    • Duration: Unlimited downloads
    • Delivery: Instant Download
     

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    Table of content:

    Title Page
    Copyright Page
    About the Authors
    Contents
    PREFACE
    CHAPTER 1 Introduction to Quantitative Analysis
    1.1 Introduction
    1.2 What Is Quantitative Analysis?
    1.3 Business Analytics
    1.4 The Quantitative Analysis Approach
    Defining the Problem
    Developing a Model
    Acquiring Input Data
    Developing a Solution
    Testing the Solution
    Analyzing the Results and Sensitivity Analysis
    Implementing the Results
    The Quantitative Analysis Approach and Modeling in the Real World
    1.5 How to Develop a Quantitative Analysis Model
    The Advantages of Mathematical Modeling
    Mathematical Models Categorized by Risk
    1.6 The Role of Computers and Spreadsheet Models in the Quantitative Analysis Approach
    1.7 Possible Problems in the Quantitative Analysis Approach
    Defining the Problem
    Developing a Model
    Acquiring Input Data
    Developing a Solution
    Testing the Solution
    Analyzing the Results
    1.8 Implementation—Not Just the Final Step
    Lack of Commitment and Resistance to Change
    Lack of Commitment by Quantitative Analysts
    Summary
    Glossary
    Key Equations
    Self-Test
    Discussion Questions and Problems
    Case Study: Food and Beverages at Southwestern University Football Games
    Bibliography
    CHAPTER 2 Probability Concepts and Applications
    2.1 Introduction
    2.2 Fundamental Concepts
    Two Basic Rules of Probability
    Types of Probability
    Mutually Exclusive and Collectively Exhaustive Events
    Unions and Intersections of Events
    Probability Rules for Unions, Intersections, and Conditional Probabilities
    2.3 Revising Probabilities with Bayes’ Theorem
    General Form of Bayes’ Theorem
    2.4 Further Probability Revisions
    2.5 Random Variables
    2.6 Probability Distributions
    Probability Distribution of a Discrete Random Variable
    Expected Value of a Discrete Probability Distribution
    Variance of a Discrete Probability Distribution
    Probability Distribution of a Continuous Random Variable
    2.7 The Binomial Distribution
    Solving Problems with the Binomial Formula
    Solving Problems with Binomial Tables
    2.8 The Normal Distribution
    Area Under the Normal Curve
    Using the Standard Normal Table
    Haynes Construction Company Example
    The Empirical Rule
    2.9 The F Distribution
    2.10 The Exponential Distribution
    Arnold’s Muffler Example
    2.11 The Poisson Distribution
    Summary
    Glossary
    Key Equations
    Solved Problems
    Self-Test
    Discussion Questions and Problems
    Case Study: WTVX
    Bibliography
    Appendix 2.1: Derivation of Bayes’ Theorem
    CHAPTER 3 Decision Analysis
    3.1 Introduction
    3.2 The Six Steps in Decision Making
    3.3 Types of Decision-Making Environments
    3.4 Decision Making Under Uncertainty
    Optimistic
    Pessimistic
    Criterion of Realism (Hurwicz Criterion)
    Equally Likely (Laplace)
    Minimax Regret
    3.5 Decision Making Under Risk
    Expected Monetary Value
    Expected Value of Perfect Information
    Expected Opportunity Loss
    Sensitivity Analysis
    3.6 A Minimization Example
    3.7 Using Software for Payoff Table Problems
    QM for Windows
    Excel QM
    3.8 Decision Trees
    Efficiency of Sample Information
    Sensitivity Analysis
    3.9 How Probability Values Are Estimated by Bayesian Analysis
    Calculating Revised Probabilities
    Potential Problem in Using Survey Results
    3.10 Utility Theory
    Measuring Utility and Constructing a Utility Curve
    Utility as a Decision-Making Criterion
    Summary
    Glossary
    Key Equations
    Solved Problems
    Self-Test
    Discussion Questions and Problems
    Case Study: Starting Right Corporation
    Case Study: Blake Electronics
    Bibliography
    CHAPTER 4 Regression Models
    4.1 Introduction
    4.2 Scatter Diagrams
    4.3 Simple Linear Regression
    4.4 Measuring the Fit of the Regression Model
    Coefficient of Determination
    Correlation Coefficient
    4.5 Assumptions of the Regression Model
    Estimating the Variance
    4.6 Testing the Model for Significance
    Triple A Construction Example
    The Analysis of Variance (ANOVA) Table
    Triple A Construction ANOVA Example
    4.7 Using Computer Software for Regression
    Excel 2013
    Excel QM
    QM for Windows
    4.8 Multiple Regression Analysis
    Evaluating the Multiple Regression Model
    Jenny Wilson Realty Example
    4.9 Binary or Dummy Variables
    4.10 Model Building
    Stepwise Regression
    Multicollinearity
    4.11 Nonlinear Regression
    4.12 Cautions and Pitfalls in Regression Analysis
    Summary
    Glossary
    Key Equations
    Solved Problems
    Self-Test
    Discussion Questions and Problems
    Case Study: North–South Airline
    Bibliography
    Appendix 4.1: Formulas for Regression Calculations
    CHAPTER 5 Forecasting
    5.1 Introduction
    5.2 Types of Forecasting Models
    Qualitative Models
    Causal Models
    Time-Series Models
    5.3 Components of a Time-Series
    5.4 Measures of Forecast Accuracy
    5.5 Forecasting Models—Random Variations Only
    Moving Averages
    Weighted Moving Averages
    Exponential Smoothing
    Using Software for Forecasting Time Series
    5.6 Forecasting Models—Trend and Random Variations
    Exponential Smoothing with Trend
    Trend Projections
    5.7 Adjusting for Seasonal Variations
    Seasonal Indices
    Calculating Seasonal Indices with No Trend
    Calculating Seasonal Indices with Trend
    5.8 Forecasting Models—Trend, Seasonal, and Random Variations
    The Decomposition Method
    Software for Decomposition
    Using Regression with Trend and Seasonal Components
    5.9 Monitoring and Controlling Forecasts
    Adaptive Smoothing
    Summary
    Glossary
    Key Equations
    Solved Problems
    Self-Test
    Discussion Questions and Problems
    Case Study: Forecasting Attendance at SWU Football Games
    Case Study: Forecasting Monthly Sales
    Bibliography
    CHAPTER 6 Inventory Control Models
    6.1 Introduction
    6.2 Importance of Inventory Control
    Decoupling Function
    Storing Resources
    Irregular Supply and Demand
    Quantity Discounts
    Avoiding Stockouts and Shortages
    6.3 Inventory Decisions
    6.4 Economic Order Quantity: Determining How Much to Order
    Inventory Costs in the EOQ Situation
    Finding the EOQ
    Sumco Pump Company Example
    Purchase Cost of Inventory Items
    Sensitivity Analysis with the EOQ Model
    6.5 Reorder Point: Determining When to Order
    6.6 EOQ Without the Instantaneous Receipt Assumption
    Annual Carrying Cost for Production Run Model
    Annual Setup Cost or Annual Ordering Cost
    Determining the Optimal Production Quantity
    Brown Manufacturing Example
    6.7 Quantity Discount Models
    Brass Department Store Example
    6.8 Use of Safety Stock
    6.9 Single-Period Inventory Models
    Marginal Analysis with Discrete Distributions
    Café du Donut Example
    Marginal Analysis with the Normal Distribution
    Newspaper Example
    6.10 ABC Analysis
    6.11 Dependent Demand: The Case for Material Requirements Planning
    Material Structure Tree
    Gross and Net Material Requirements Plan
    Two or More End Products
    6.12 Just-In-Time Inventory Control
    6.13 Enterprise Resource Planning
    Summary
    Glossary
    Key Equations
    Solved Problems
    Self-Test
    Discussion Questions and Problems
    Case Study: Martin-Pullin Bicycle Corporation
    Bibliography
    Appendix 6.1: Inventory Control with QM for Windows
    CHAPTER 7 Linear Programming Models: Graphical and Computer Methods
    7.1 Introduction
    7.2 Requirements of a Linear Programming Problem
    7.3 Formulating LP Problems
    Flair Furniture Company
    7.4 Graphical Solution to an LP Problem
    Graphical Representation of Constraints
    Isoprofit Line Solution Method
    Corner Point Solution Method
    Slack and Surplus
    7.5 Solving Flair Furniture’s LP Problem Using QM for Windows, Excel 2013, and Excel QM
    Using QM for Windows
    Using Excel’s Solver Command to Solve LP Problems
    Using Excel QM
    7.6 Solving Minimization Problems
    Holiday Meal Turkey Ranch
    7.7 Four Special Cases in LP
    No Feasible Solution
    Unboundedness
    Redundancy
    Alternate Optimal Solutions
    7.8 Sensitivity Analysis
    High Note Sound Company
    Changes in the Objective Function Coefficient
    QM for Windows and Changes in Objective Function Coefficients
    Excel Solver and Changes in Objective Function Coefficients
    Changes in the Technological Coefficients
    Changes in the Resources or Right-Hand-Side Values
    QM for Windows and Changes in Right-Hand-Side Values
    Excel Solver and Changes in Right-Hand-Side Values
    Summary
    Glossary
    Solved Problems
    Self-Test
    Discussion Questions and Problems
    Case Study: Mexicana Wire Works
    Bibliography
    CHAPTER 8 Linear Programming Applications
    8.1 Introduction
    8.2 Marketing Applications
    Media Selection
    Marketing Research
    8.3 Manufacturing Applications
    Production Mix
    Production Scheduling
    8.4 Employee Scheduling Applications
    Labor Planning
    8.5 Financial Applications
    Portfolio Selection
    Truck Loading Problem
    8.6 Ingredient Blending Applications
    Diet Problems
    Ingredient Mix and Blending Problems
    8.7 Other Linear Programming Applications
    Summary
    Self-Test
    Problems
    Case Study: Cable & Moore
    Bibliography
    CHAPTER 9 Transportation, Assignment, and Network Models
    9.1 Introduction
    9.2 The Transportation Problem
    Linear Program for the Transportation Example
    Solving Transportation Problems Using Computer Software
    A General LP Model for Transportation Problems
    Facility Location Analysis
    9.3 The Assignment Problem
    Linear Program for Assignment Example
    9.4 The Transshipment Problem
    Linear Program for Transshipment Example
    9.5 Maximal-Flow Problem
    Example
    9.6 Shortest-Route Problem
    9.7 Minimal-Spanning Tree Problem
    Summary
    Glossary
    Solved Problems
    Self-Test
    Discussion Questions and Problems
    Case Study: Andrew–Carter, Inc.
    Case Study: Northeastern Airlines
    Case Study: Southwestern University Traffic Problems
    Bibliography
    Appendix 9.1: Using QM for Windows
    CHAPTER 10 Integer Programming, Goal Programming, and Nonlinear Programming
    10.1 Introduction
    10.2 Integer Programming
    Harrison Electric Company Example of Integer Programming
    Using Software to Solve the Harrison Integer Programming Problem
    Mixed-Integer Programming Problem Example
    10.3 Modeling with 0–1 (Binary) Variables
    Capital Budgeting Example
    Limiting the Number of Alternatives Selected
    Dependent Selections
    Fixed-Charge Problem Example
    Financial Investment Example
    10.4 Goal Programming
    Example of Goal Programming: Harrison Electric Company Revisited
    Extension to Equally Important Multiple Goals
    Ranking Goals with Priority Levels
    Goal Programming with Weighted Goals
    10.5 Nonlinear Programming
    Nonlinear Objective Function and Linear Constraints
    Both Nonlinear Objective Function and Nonlinear Constraints
    Linear Objective Function with Nonlinear Constraints
    Summary
    Glossary
    Solved Problems
    Self-Test
    Discussion Questions and Problems
    Case Study: Schank Marketing Research
    Case Study: Oakton River Bridge
    Bibliography
    CHAPTER 11 Project Management
    11.1 Introduction
    11.2 PERT/CPM
    General Foundry Example of PERT/CPM
    Drawing the PERT/CPM Network
    Activity Times
    How to Find the Critical Path
    Probability of Project Completion
    What PERT Was Able to Provide
    Using Excel QM for the General Foundry Example
    Sensitivity Analysis and Project Management
    11.3 PERT/Cost
    Planning and Scheduling Project Costs: Budgeting Process
    Monitoring and Controlling Project Costs
    11.4 Project Crashing
    General Foundary Example
    Project Crashing with Linear Programming
    11.5 Other Topics in Project Management
    Subprojects
    Milestones
    Resource Leveling
    Software
    Summary
    Glossary
    Key Equations
    Solved Problems
    Self-Test
    Discussion Questions and Problems
    Case Study: Southwestern University Stadium Construction
    Case Study: Family Planning Research Center of Nigeria
    Bibliography
    Appendix 11.1: Project Management with QM for Windows
    CHAPTER 12 Waiting Lines and Queuing Theory Models
    12.1 Introduction
    12.2 Waiting Line Costs
    Three Rivers Shipping Company Example
    12.3 Characteristics of a Queuing System
    Arrival Characteristics
    Waiting Line Characteristics
    Service Facility Characteristics
    Identifying Models Using Kendall Notation
    12.4 Single-Channel Queuing Model with Poisson Arrivals and Exponential Service Times (M/M/1)
    Assumptions of the Model
    Queuing Equations
    Arnold’s Muffler Shop Case
    Enhancing the Queuing Environment
    12.5 Multichannel Queuing Model with Poisson Arrivals and Exponential Service Times (M/M/m)
    Equations for the Multichannel Queuing Model
    Arnold’s Muffler Shop Revisited
    12.6 Constant Service Time Model (M/D/1)
    Equations for the Constant Service Time Model
    Garcia-Golding Recycling, Inc.
    12.7 Finite Population Model (M/M/1 with Finite Source)
    Equations for the Finite Population Model
    Department of Commerce Example
    12.8 Some General Operating Characteristic Relationships
    12.9 More Complex Queuing Models and the Use of Simulation
    Summary
    Glossary
    Key Equations
    Solved Problems
    Self-Test
    Discussion Questions and Problems
    Case Study: New England Foundry
    Case Study: Winter Park Hotel
    Bibliography
    Appendix 12.1: Using QM for Windows
    CHAPTER 13 Simulation Modeling
    13.1 Introduction
    13.2 Advantages and Disadvantages of Simulation
    13.3 Monte Carlo Simulation
    Harry’s Auto Tire Example
    Using QM for Windows for Simulation
    Simulation with Excel Spreadsheets
    13.4 Simulation and Inventory Analysis
    Simkin’s Hardware Store
    Analyzing Simkin’s Inventory Costs
    13.5 Simulation of a Queuing Problem
    Port of New Orleans
    Using Excel to Simulate the Port of New Orleans Queuing Problem
    13.6 Simulation Model for a Maintenance Policy
    Three Hills Power Company
    Cost Analysis of the Simulation
    13.7 Other Simulation Issues
    Two Other Types of Simulation Models
    Verification and Validation
    Role of Computers in Simulation
    Summary
    Glossary
    Solved Problems
    Self-Test
    Discussion Questions and Problems
    Case Study: Alabama Airlines
    Case Study: Statewide Development Corporation
    Case Study: FB Badpoore Aerospace
    Bibliography
    CHAPTER 14 Markov Analysis
    14.1 Introduction
    14.2 States and State Probabilities
    The Vector of State Probabilities for Three Grocery Stores Example
    14.3 Matrix of Transition Probabilities
    Transition Probabilities for the Three Grocery Stores
    14.4 Predicting Future Market Shares
    14.5 Markov Analysis of Machine Operations
    14.6 Equilibrium Conditions
    14.7 Absorbing States and the Fundamental Matrix: Accounts Receivable Application
    Summary
    Glossary
    Key Equations
    Solved Problems
    Self-Test
    Discussion Questions and Problems
    Case Study: Rentall Trucks
    Bibliography
    Appendix 14.1: Markov Analysis with QM for Windows
    Appendix 14.2: Markov Analysis With Excel
    CHAPTER 15 Statistical Quality Control
    15.1 Introduction
    15.2 Defining Quality and TQM
    15.3 Statiscal Process Control
    Variability in the Process
    15.4 Control Charts for Variables
    The Central Limit Theorem
    Setting x-Chart Limits
    Setting Range Chart Limits
    15.5 Control Charts for Attributes
    p-Charts
    c-Charts
    Summary
    Glossary
    Key Equations
    Solved Problems
    Self-Test
    Discussion Questions and Problems
    Bibliography
    Appendix 15.1: Using QM for Windows for SPC
    APPENDICES
    APPENDIX A Areas Under the Standard
    APPENDIX B Binomial Probabilities
    APPENDIX C Values of e-Λ for Use in the Poisson Distribution
    APPENDIX D F Distribution Values
    APPENDIX E Using POM-QM for Windows
    APPENDIX F Using Excel QM and Excel Add-Ins
    APPENDIX G Solutions to Selected Problems
    APPENDIX H Solutions to Self-Tests
    INDEX

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