Quantitative Methods for Business 13th edition

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David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran, Michael J. Fry, and Jeffrey W. Ohlmann
Publisher: Cengage Learning

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  • Anderson Quantitative Methods for Business 13e - Homework and Quizzes

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  • Chapter 1: Introduction
    • 1.1: Problem Solving and Decision Making
    • 1.2: Quantitative Analysis and Decision Making
    • 1.3: Quantitative Analysis
    • 1.4: Models of Cost, Revenue, and Profit
    • 1.5: Quantitative Methods in Practice
    • 1: Exercises
    • 1: Case Problems
    • 1: Test Bank

  • Chapter 2: Introduction to Probability
    • 2.1: Experiments and the Sample Space
    • 2.2: Assigning Probabilities to Experimental Outcomes
    • 2.3: Events and Their Probabilities
    • 2.4: Some Basic Relationships of Probability
    • 2.5: Bayes' Theorem
    • 2.6: Simpson's Paradox
    • 2: Exercises
    • 2: Case Problems
    • 2: Exploring Analytics Applet Exercises
    • 2: Test Bank

  • Chapter 3: Probability Distributions
    • 3.1: Random Variables
    • 3.2: Discrete Random Variables
    • 3.3: Binomial Probability Distribution
    • 3.4: Poisson Probability Distribution
    • 3.5: Continuous Random Variables
    • 3.6: Normal Probability Distribution
    • 3.7: Exponential Probability Distribution
    • 3: Exercises
    • 3: Case Problems
    • 3: Exploring Analytics Applet Exercises
    • 3: Test Bank

  • Chapter 4: Decision Analysis
    • 4.1: Problem Formulation
    • 4.2: Decision Making Without Probabilities
    • 4.3: Decision Making with Probabilities
    • 4.4: Risk Analysis and Sensitivity Analysis
    • 4.5: Decision Analysis with Sample Information
    • 4.6: Computing Branch Probabilities with Bayes' Theorem
    • 4: Exercises
    • 4: Case Problems
    • 4: Test Bank

  • Chapter 5: Utility and Game Theory
    • 5.1: The Meaning of Utility
    • 5.2: Utility and Decision Making
    • 5.3: Utility: Other Considerations
    • 5.4: Introduction to Game Theory
    • 5.5: Mixed Strategy Games
    • 5: Exercises
    • 5: Case Problems
    • 5: Test Bank

  • Chapter 6: Time Series Analysis and Forecasting
    • 6.1: Time Series Patterns
    • 6.2: Forecast Accuracy
    • 6.3: Moving Averages and Exponential Smoothing
    • 6.4: Linear Trend Projection
    • 6.5: Seasonality
    • 6: Exercises
    • 6: Case Problems
    • 6: Exploring Analytics Applet Exercises
    • 6: Test Bank

  • Chapter 7: Introduction to Linear Programming
    • 7.1: A Simple Maximization Problem
    • 7.2: Graphical Solution Procedure
    • 7.3: Extreme Points and the Optimal Solution
    • 7.4: Computer Solution of the RMC Problem
    • 7.5: A Simple Minimization Problem
    • 7.6: Special Cases
    • 7.7: General Linear Programming Notation
    • 7: Exercises
    • 7: Case Problems
    • 7: Exploring Analytics Applet Exercises
    • 7: Test Bank

  • Chapter 8: Linear Programming: Sensitivity Analysis and Interpretation of Solution
    • 8.1: Introduction to Sensitivity Analysis
    • 8.2: Objective Function Coefficients
    • 8.3: Right-Hand Sides
    • 8.4: Limitations of Classical Sensitivity Analysis
    • 8.5: More Than Two Decision Variables
    • 8.6: Electronic Communications Problem
    • 8: Exercises
    • 8: Case Problems
    • 8: Test Bank

  • Chapter 9: Linear Programming Applications in Marketing, Finance, and Operations Management
    • 9.1: Marketing Applications
    • 9.2: Financial Applications
    • 9.3: Operations Management Applications
    • 9: Exercises
    • 9: Case Problems
    • 9: Test Bank
    • 9: Test Bank

  • Chapter 10: Distribution and Network Models
    • 10.1: Supply Chain Models
    • 10.2: Assignment Problem
    • 10.3: Shortest-Route Problem
    • 10.4: Maximal Flow Problem
    • 10.5: A Production and Inventory Application
    • 10: Exercises
    • 10: Case Problems
    • 10: Test Bank

  • Chapter 11: Integer Linear Programming
    • 11.1: Types of Integer Linear Programming Models
    • 11.2: Graphical and Computer Solutions for an All-Integer Linear Program
    • 11.3: Applications Involving 0–1 Variables
    • 11.4: Modeling Flexibility Provided by 0–1 Integer Variables
    • 11: Exercises
    • 11: Case Problems
    • 11: Exploring Analytics Applet Exercises
    • 11: Test Bank

  • Chapter 12: Advanced Optimization Applications
    • 12.1: Data Envelopment Analysis
    • 12.2: Revenue Management
    • 12.3: Portfolio Models and Asset Allocation
    • 12.4: Nonlinear Optimization—The RMC Problem Revisited
    • 12.5: Constructing an Index Fund
    • 12: Exercises
    • 12: Case Problems
    • 12: Exploring Analytics Applet Exercises
    • 12: Test Bank

  • Chapter 13: Project Scheduling: PERT/CPM
    • 13.1: Project Scheduling Based on Expected Activity Times
    • 13.2: Project Scheduling Considering Uncertain Activity Times
    • 13.3: Considering Time–Cost Trade-Offs
    • 13: Exercises
    • 13: Case Problems
    • 13: Test Bank

  • Chapter 14: Inventory Models
    • 14.1: Economic Order Quantity (EOQ) Model
    • 14.2: Economic Production Lot Size Model
    • 14.3: Inventory Model with Planned Shortages
    • 14.4: Quantity Discounts for the EOQ Model
    • 14.5: Single-Period Inventory Model with Probabilistic Demand
    • 14.6: Order-Quantity, Reorder Point Model with Probabilistic Demand
    • 14.7: Periodic Review Model with Probabilistic Demand
    • 14: Exercises
    • 14: Case Problems
    • 14: Test Bank

  • Chapter 15: Waiting Line Models
    • 15.1: Structure of a Waiting Line System
    • 15.2: Single-Server Waiting Line Model with Poisson Arrivals and Exponential Service Times
    • 15.3: Multiple-Server Waiting Line Model with Poisson Arrivals and Exponential Service Times
    • 15.4: Some General Relationships for Waiting Line Models
    • 15.5: Economic Analysis of Waiting Lines
    • 15.6: Other Waiting Line Models
    • 15.7: Single-Server Waiting Line Model with Poisson Arrivals and Arbitrary Service Times
    • 15.8: Multiple-Server Model with Poisson Arrivals, Arbitrary Service Times, and No Waiting Line
    • 15.9: Waiting Line Models with Finite Calling Populations
    • 15: Exercises
    • 15: Case Problems
    • 15: Test Bank

  • Chapter 16: Simulation
    • 16.1: What-If Analysis
    • 16.2: Simulation of Sanotronics Problem
    • 16.3: Inventory Simulation
    • 16.4: Waiting Line Simulation
    • 16.5: Simulation Considerations
    • 16: Exercises
    • 16: Case Problems
    • 16: Test Bank

  • Chapter 17: Markov Processes
    • 17.1: Market Share Analysis
    • 17.2: Accounts Receivable Analysis
    • 17: Exercises
    • 17: Case Problems
    • 17: Test Bank

  • Chapter A: Appendix
    • A: Appendix A: Building Spreadsheet Models

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Group Quantity Questions
Chapter 1: Introduction
1 0  
Chapter 2: Introduction to Probability
2 0  
Chapter 3: Probability Distributions
3 0  
Chapter 4: Decision Analysis
4 0  
Chapter 5: Utility and Game Theory
5 0  
Chapter 6: Time Series Analysis and Forecasting
6 0  
Chapter 7: Introduction to Linear Programming
7 0  
Chapter 8: Linear Programming: Sensitivity Analysis and Interpretation of Solution
8 0  
Chapter 9: Linear Programming Applications in Marketing, Finance, and Operations Management
9 0  
Chapter 10: Distribution and Network Models
10 0  
Chapter 11: Integer Linear Programming
11 0  
Chapter 12: Advanced Optimization Applications
12 0  
Chapter 13: Project Scheduling: PERT/CPM
13 0  
Chapter 14: Inventory Models
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Chapter 15: Waiting Line Models
15 0  
Chapter 16: Simulation
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Chapter 17: Markov Processes
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Total 0