# Quantitative Methods for Business 13th edition

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 (12)
• 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: Exercises (17)
• 2: Case Problems (1)
• 2: Exploring Analytics Applet Exercises (2)
• 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 (25)
• 3: Case Problems (1)
• 3: Exploring Analytics Applet Exercises (5)
• 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 (23)
• 4: Case Problems (1)
• 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 (9)
• 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 (36)
• 6: Case Problems (4)
• 6: Exploring Analytics Applet Exercises (3)
• 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 (33)
• 7: Case Problems
• 7: Exploring Analytics Applet Exercises (2)
• 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 (19)
• 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 (12)
• 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 (20)
• 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 (14)
• 11: Case Problems
• 11: Exploring Analytics Applet Exercises (2)
• 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 (15)
• 12: Case Problems
• 12: Exploring Analytics Applet Exercises (1)
• 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: Exercises (13)
• 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 (18)
• 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 (23)
• 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 (8)
• 16: Case Problems
• 16: Test Bank

• Chapter 17: Markov Processes
• 17.1: Market Share Analysis
• 17.2: Accounts Receivable Analysis
• 17: Exercises (8)
• 17: Case Problems
• 17: Test Bank

• Chapter A: Appendix
• A: Appendix A: Building Spreadsheet Models (11)

Provide a conceptual understanding of the critical role of quantitative methods in decision-making with Anderson/Sweeney/Williams/Camm/Cochran/Fry/Ohlmann's best-selling Quantitative Methods for Business, 13th edition. Written for the non-mathematician, a unique applications orientation introduces quantitative methods, how they work, and how decision makers can apply and interpret data. A strong managerial emphasis highlights real examples while a problem-scenario approach helps readers apply mathematical concepts. This edition explains how to construct a spreadsheet simulation model using only native Excel functions, as well as how to use Excel add-ins for more sophisticated simulation analyses. Excel® worksheets, TreePlan, Crystal Ball, Premium Solver for Excel® and LINGO are available. Additionally, an all new WebAssign online course management system is available with this powerful business statistics solution.

#### Features:

• Watch It links provide step-by-step instruction with short, engaging videos that are ideal for visual learners.
• Master It Tutorials (MI) show how to solve a similar problem in multiple steps by providing direction along with derivation so students understand the concepts and reasoning behind the problem solving.
• All questions contain detailed solutions to the problem, available to students at your discretion.
• Case Problems (CP) allow students to work on more extensive problems related to the chapter material and work with larger data sets.
• Exploring Analytics Applet (AQ) problems ask students to answer questions using linked interactive statistical analysis applets.
• Downloadable DATAfiles (Excel and CSV), Appendix A: Building Spreadsheet Models, Appendix B: Binomial Probabilities, Appendix C: Poission Probabilities, Appendix E: Values of e, and Appendix G: Self-Test Solutions and Even-Numbered Answers will be available as textbook resources for students and instructors.

## Questions Available within WebAssign

Most questions from this textbook are available in WebAssign. The online questions are identical to the textbook questions except for minor wording changes necessary for Web use. Whenever possible, variables, numbers, or words have been randomized so that each student receives a unique version of the question. This list is updated nightly.

##### Question Group Key
E - End of Chapter Exercise
MI - Master It
MI.SA - Stand Alone Master It
CP - Case Problem
AQ - Exploring Statistics and Analytics Applet
ET - Excel Tutorial

##### Question Availability Color Key
BLACK questions are available now
GRAY questions are under development

Group Quantity Questions
Chapter A: Appendix
A.ET 11 001 002 003 004 005 006 007 008 009 010 011
Chapter 1: Introduction
1.E 12 001 003 004 005 007 008 009 011 012 013 015 017
Chapter 2: Introduction to Probability
2.AQ 2 501a 501b
2.CP 1 001
2.E 17 001 003 005 007 009 011 012.MI 012.MI.SA 015 017 019.MI 019.MI.SA 020 021 023 027 029
Chapter 3: Probability Distributions
3.AQ 5 501 502a 502b 502c 503
3.CP 1 001
3.E 25 001 002.MI 002.MI.SA 004.MI 004.MI.SA 007.MI 007.MI.SA 008 009 010 012 013 014 015.MI 015.MI.SA 017 018 019 020 021 022 023 029 031.MI 031.MI.SA
Chapter 4: Decision Analysis
4.CP 1 001
4.E 23 001.MI 001.MI.SA 003 004 006.MI 006.MI.SA 007 008 009 011 013 014 015 016 017 018 019 020 021 023.MI 023.MI.SA 024 025
Chapter 5: Utility and Game Theory
5.E 9 001 003 005 007 009 011 013 015 017
Chapter 6: Time Series Analysis and Forecasting
6.AQ 3 501 502 503
6.CP 4 001 001.alt 002 002.alt
6.E 36 001 002 003 004.MI 004.MI.SA 005 006 007 007.alt 008 008.alt 009 010 011.MI 011.MI.SA 012 013 014 015 015.alt 017.MI 017.MI.SA 018 019 021 021.alt 023 023.alt 024 025 026 026.alt 027 027.alt 028 028.alt
Chapter 7: Introduction to Linear Programming
7.AQ 2 501a 501b
7.E 33 001 002 003 005 006 007 009 010 011 013 015 017 019 021 023 024 025 027 029 031 033 034 035 037 039 041 042 043 045 047 049 051 053
Chapter 8: Linear Programming: Sensitivity Analysis and Interpretation of Solution
8.E 19 001 002 003 005 006 007 009 011 012 013 015 017 019 021 023 025 027 029 031
Chapter 9: Linear Programming Applications in Marketing, Finance, and Operations Management
9.E 12 001 003 005 007 009 011 013 015 017 019 023 025
Chapter 10: Distribution and Network Models
10.E 20 001 002 003 005 006 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035
Chapter 11: Integer Linear Programming
11.AQ 2 501a 501b
11.E 14 001 002 003 005 007 009 011 013 015 017 019 021 023 025