Quantitative Analysis for Management, 13/e

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Book description

Foundational understanding of management science through real-world problems and solutions

Quantitative Analysis for Management helps readers to develop a real-world understanding of business analytics, quantitative methods, and management science by emphasizing model building, tangible examples, and computer applications. The authors offer an accessible introduction to mathematical models and then readers apply those models using step-by-step, how-to instructions. For more intricate mathematical procedures, the 13th Edition offers a flexible approach, allowing readers to omit specific sections without interrupting the flow of the material.

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Quantitative Analysis for Management
About the Authors
Brief Contents
Contents
Preface
1. Overview
2. Special Features
3. Significant Changes to the Thirteenth Edition
4. Online Modules
5. Software
6. Companion Website
7. Instructor Resources
1. Learning Objectives
2. 1.1 What Is Quantitative Analysis?
3. 1.2 Business Analytics
4. 1.3 The Quantitative Analysis Approach
  1. Defining the Problem
  2. Developing a Model
  3. Acquiring Input Data
  4. Developing a Solution
  5. Testing the Solution
  6. Analyzing the Results and Sensitivity Analysis
  7. Implementing the Results
  8. The Quantitative Analysis Approach and Modeling in the Real World
  1. The Advantages of Mathematical Modeling
  2. Mathematical Models Categorized by Risk
  1. Defining the Problem
    1. Conflicting Viewpoints
    2. Impact on Other Departments
    3. Beginning Assumptions
    4. Solution Outdated
    1. Fitting the Textbook Models
    2. Understanding the Model
    1. Using Accounting Data
    2. Validity of Data
    1. Hard-to-Understand Mathematics
    2. Only One Answer is Limiting
    1. Lack of Commitment and Resistance to Change
    2. Lack of Commitment by Quantitative Analysts
    1. Discussion Questions
    2. Problems
    1. Learning Objectives
    2. 2.1 Fundamental Concepts
      1. Two Basic Rules of Probability
      2. Types of Probability
      3. Mutually Exclusive and Collectively Exhaustive Events
      4. Unions and Intersections of Events
      5. Probability Rules for Unions, Intersections, and Conditional Probabilities
      1. General Form of Bayes’ Theorem
      1. Probability Distribution of a Discrete Random Variable
      2. Expected Value of a Discrete Probability Distribution
      3. Variance of a Discrete Probability Distribution
      4. Probability Distribution of a Continuous Random Variable
      1. Solving Problems with the Binomial Formula
      2. Solving Problems with Binomial Tables
      1. Area Under the Normal Curve
      2. Using the Standard Normal Table
      3. Haynes Construction Company Example
      4. The Empirical Rule
      1. Arnold’s Muffler Example
      1. Solution
      2. Solution
      3. Solution
      4. Solution
      5. Solution
      6. Solution
      7. Solution
      8. Solution
      1. Discussion Questions
      2. Problems
      1. Learning Objectives
      2. 3.1 The Six Steps in Decision Making
      3. 3.2 Types of Decision-Making Environments
      4. 3.3 Decision Making Under Uncertainty
        
        Optimistic
        
        Pessimistic
        
        Criterion of Realism (Hurwicz Criterion)
        
        Equally Likely (Laplace)
        
        Minimax Regret
        
        Expected Monetary Value
        
        Expected Value of Perfect Information
        
        Expected Opportunity Loss
        
        Sensitivity Analysis
        
        A Minimization Example
        
        QM for Windows
        
        Excel QM
        
        Efficiency of Sample Information
        
        Sensitivity Analysis
        
        Calculating Revised Probabilities
        
        Potential Problem in Using Survey Results
        
        Measuring Utility and Constructing a Utility Curve
        
        Utility as a Decision-Making Criterion
        
        Solution
        
        Solution
        
        Solution
        
        Solution
        
        Discussion Questions
        
        Problems
        
        Learning Objectives
        
        4.1 Scatter Diagrams
        
        4.2 Simple Linear Regression
        
        4.3 Measuring the Fit of the Regression Model
        
        Coefficient of Determination
        
        Correlation Coefficient
        
        Estimating the Variance
        
        Triple A Construction Example
        
        The Analysis of Variance (ANOVA) Table
        
        Triple A Construction ANOVA Example
        
        Excel 2016
        
        Excel QM
        
        QM for Windows
        
        Evaluating the Multiple Regression Model
        
        Jenny Wilson Realty Example
        
        Stepwise Regression
        
        Multicollinearity
        
        Solution
        
        Solution
        
        Discussion Questions
        
        Problems
        
        Learning Objectives
        
        5.1 Types of Forecasting Models
        
        Qualitative Models
        
        Causal Models
        
        Time-Series Models
        
        Moving Averages
        
        Wallace Garden Supply Example
        
        Getting Started
        
        Port of Baltimore Example
        
        Exponential Smoothing with Trend
        
        Trend Projections
        
        Seasonal Indices
        
        Calculating Seasonal Indices with No Trend
        
        Calculating Seasonal Indices with Trend
        
        The Decomposition Method
        
        Software for Decomposition
        
        Using Regression with Trend and Seasonal Components
        
        Adaptive Smoothing
        
        Solution
        
        Solution
        
        Discussion Questions
        
        Problems
        
        Bibliography
        
        Learning Objectives
        
        6.1 Importance of Inventory Control
        
        Decoupling Function
        
        Storing Resources
        
        Irregular Supply and Demand
        
        Quantity Discounts
        
        Avoiding Stockouts and Shortages
        
        Inventory Costs in the EOQ Situation
        
        Finding the EOQ
        
        Sumco Pump Company Example
        
        Using Excel QM for Basic EOQ Inventory Problems
        
        Annual Carrying Cost for Production Run Model
        
        Annual Setup Cost or Annual Ordering Cost
        
        Determining the Optimal Production Quantity
        
        Brown Manufacturing Example
        
        Using Excel QM for Production Run Models
        
        Brass Department Store Example
        
        Using Excel QM for Quantity Discount Problems
        
        Marginal Analysis with Discrete Distributions
        
        Café du Donut Example
        
        Marginal Analysis with the Normal Distribution
        
        Newspaper Example
        
        Material Structure Tree
        
        Gross and Net Material Requirements Plans
        
        Two or More End Products
        
        Solution
        
        Solution
        
        Solution
        
        Solution
        
        Solution
        
        Discussion Questions
        
        Problems
        
        Bibliography
        
        Appendix 6.1: Inventory Control with QM for Windows
        
        Learning Objectives
        
        7.1 Requirements of a Linear Programming Problem
        
        7.2 Formulating LP Problems
        
        Flair Furniture Company
        
        Graphical Representation of Constraints
        
        Isoprofit Line Solution Method
        
        Using QM for Windows
        
        Using Excel’s Solver Command to Solve LP Problems
        
        Preparing the Spreadsheet For Solver
        
        Using Solver
        
        Holiday Meal Turkey Ranch
        
        Using The Corner Point Method On A Minimization Problem
        
        Isocost Line Approach
        
        No Feasible Solution
        
        Unboundedness
        
        Redundancy
        
        Alternate Optimal Solutions
        
        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
        
        Solution
        
        Solution
        
        Solution
        
        Solution
        
        Discussion Questions
        
        Problems
        
        Bibliography
        
        Learning Objectives
        
        8.1 Marketing Applications
        
        Media Selection
        
        Marketing Research
        
        Production Mix
        
        Production Scheduling
        
        Labor Planning
        
        Portfolio Selection
        
        Truck Loading Problem
        
        Diet Problems
        
        Ingredient Mix and Blending Problems
        
        Learning Objectives
        
        9.1 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
        
        Linear Program for Assignment Example
        
        Linear Program for Transshipment Example
        
        Solution
        
        Discussion Questions
        
        Problems*
        
        Bibliography
        
        Appendix 9.1: Using QM for Windows
        
        Learning Objectives
        
        10.1 Integer Programming
        
        Harrison Electric Company Example of Integer Programming
        
        Using Software to Solve the Harrison Integer Programming Problem
        
        Mixed-Integer Programming Problem Example
        
        Using QM For Windows And Excel to Solve Bagwell’s Integer Programming Model
        
        Capital Budgeting Example
        
        Limiting the Number of Alternatives Selected
        
        Dependent Selections
        
        Fixed-Charge Problem Example
        
        Financial Investment Example
        
        Extension to Equally Important Multiple Goals
        
        Ranking Goals with Priority Levels
        
        Goal Programming with Weighted Goals
        
        Using QM For Windows To Solve Harrison’s Problem
        
        Nonlinear Objective Function and Linear Constraints
        
        Both Nonlinear Objective Function and Nonlinear Constraints
        
        Linear Objective Function with Nonlinear Constraints
        
        Solution
        
        Solution
        
        Solution
        
        Discussion Questions
        
        Problems
        
        Bibliography
        
        Learning Objectives
        
        11.1 PERT/CPM
        
        General Foundry Example of PERT/CPM
        
        Drawing the PERT/CPM Network
        
        Activity Times
        
        How to Find the Critical Path
        
        Earliest Times
        
        Latest Times
        
        Concept Of Slack In Critical Path Computations
        
        Planning and Scheduling Project Costs: Budgeting Process
        
        Budgeting For General Foundry
        
        General Foundry Example
        
        Project Crashing with Linear Programming
        
        Objective Function
        
        Crash Time Constraints
        
        Project Completion Constraint
        
        Constraints Describing The Network
        
        Subprojects
        
        Milestones
        
        Resource Leveling
        
        Software
        
        Solution
        
        Solution
        
        Discussion Questions
        
        Problems
        
        Discussion Question
        
        Learning Objectives
        
        12.1 Waiting Line Costs
        
        Three Rivers Shipping Company Example
        
        Arrival Characteristics
        
        Size Of The Calling Population
        
        Pattern Of Arrivals At The System
        
        Behavior Of The Arrivals
        
        Basic Queuing System Configurations
        
        Service Time Distribution
        
        Assumptions of the Model
        
        Queuing Equations
        
        Arnold’s Muffler Shop Case
        
        Using Excel QM On The Arnold’s Muffler Shop Queue
        
        Introducing Costs Into The Model
        
        Equations for the Multichannel Queuing Model
        
        Arnold’s Muffler Shop Revisited
        
        Using Excel QM For Analysis Of Arnold’s Multichannel Queuing Model
        
        Equations for the Constant Service Time Model
        
        Garcia-Golding Recycling, Inc.
        
        Using Excel QM For Garcia-Golding’s Constant Service Time Model
        
        Equations for the Finite Population Model
        
        Department of Commerce Example
        
        Solving The Department Of Commerce Finite Population Model With Excel QM
        
        Solution
        
        Solution
        
        Solution
        
        Solution
        
        Discussion Questions
        
        Problems
        
        Learning Objectives
        
        13.1 Advantages and Disadvantages of Simulation
        
        13.2 Monte Carlo Simulation
        
        Harry’s Auto Tire Example
        
        Step 1: Establishing Probability Distributions.
        
        Step 2: Building a Cumulative Probability Distribution for Each Variable.
        
        Step 3: Setting Random Number Intervals.
        
        Step 4: Generating Random Numbers.
        
        Step 5: Simulating the Experiment.
        
        Simkin’s Hardware Store
        
        Analyzing Simkin’s Inventory Costs
        
        Port of New Orleans
        
        Using Excel to Simulate the Port of New Orleans Queuing Problem
        
        Three Hills Power Company
        
        Column 1: Breakdown Number
        
        Column 2: Random Number for Breakdowns
        
        Column 3: Time Between Breakdowns
        
        Column 4: Time of Breakdown
        
        Column 5: Time Repairperson Is Free to Begin Repair
        
        Column 6: Random Number for Repair Time
        
        Column 7: Repair Time Required
        
        Column 8: Time Repair Ends
        
        Column 9: Number of Hours the Machine Is Down
        
        Building An Excel Simulation Model For Three Hills Power Company
        
        Two Other Types of Simulation Models
        
        Operational Gaming
        
        Systems Simulation
        
        Solution
        
        Solution
        
        Discussion Questions
        
        Problems
        
        Learning Objectives
        
        14.1 States and State Probabilities
        
        The Vector of State Probabilities for Grocery Store Example
        
        Transition Probabilities for Grocery Store Example
        
        Solution
        
        Solution
        
        Discussion Questions
        
        Problems
        
        Learning Objectives
        
        15.1 Defining Quality and TQM
        
        15.2 Statistical Process Control
        
        Variability in the Process
        
        Building Control Charts
        
        Natural Variations
        
        Assignable Variations
        
        The Central Limit Theorem
        
        Setting X -Chart Limits
        
        Box-Filling Example
        
        Using Excel QM For Box-Filling Example
        
        Super Cola Example
        
        Using Excel QM For Super Cola Example
        
        Range Example
        
        p-Charts
        
        ARCO p-Chart Example
        
        Using Excel QM For p-Charts
        
        Red Top Cab Company c-Chart Example
        
        Using Excel QM For c-Charts
        
        Solution
        
        Solution
        
        Solution
        
        Discussion Questions
        
        Problems
        
        Appendix A: Areas Under the Standard Normal Curve
        
        A
        
        B
        
        C
        
        D
        
        E
        
        F
        
        G
        
        H
        
        I
        
        J
        
        K
        
        L
        
        M
        
        N
        
        O
        
        P
        
        Q
        
        R
        
        S
        
        T
        
        U
        
        V
        
        W
        
        X
        
        Z
        
        Learning Objectives
        
        M3.1 Break-Even Analysis and the Normal Distribution
        
        Barclay Brothers Company’s New Product Decision
        
        Probability Distribution of Demand
        
        Using Expected Monetary Value to Make a Decision
        
        Opportunity Loss Function
        
        Expected Opportunity Loss
        
        Solution
        
        Solution
        
        Discussion Questions
        
        Problems
        
        Learning Objectives
        
        M4.1 Language of Games
        
        M4.2 The Minimax Criterion
        
        M4.3 Pure Strategy Games
        
        M4.4 Mixed Strategy Games
        
        M4.5 Dominance
        
        Summary
        
        Glossary
        
        Solved Problems
        
        Solution
        
        Solution
        
        Discussion Questions
        
        Problems
        
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        Product information
        
        Title: Quantitative Analysis for Management, 13/e
        
        Author(s): Barry Render, Ralph M. Stair, Michael E. Hanna, Trevor S. Hale
        
        Release date: January 2017
        
        Publisher(s): Pearson
        
        ISBN: 9780134543161