# Quantitative Analysis for Management, 14th edition

• Barry Render,
• Ralph M. Stair,
• Michael E. Hanna,
• Trevor S. Hale

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## Overview

### Hallmark features of this title

• A flexible approach lets instructors omit sections or intricate mathematical procedures, without interrupting the flow of material.
• Excel is used to solve problems in the text. An Excel QM Add-in helps students perform calculations with Excel and improve their skills. POM-QM for Windows is a powerful software package specifically for QM that uses the full capabilities of Windows to solve problems.
• Procedure boxes summarize complex quantitative techniques, presenting them as digestible steps.
• QA in Action boxes show how real companies use quantitative analysis to solve issues.
• Solved Problems, Discussion Questions, and Self Tests test students’ comprehension.
• A Companion Website (pearson.com/render) provides online-only modules, and additional problems and cases.

ISBN-13: 9780138170851

Subject: Management

Category: Management Science

1. Introduction to Quantitative Analysis
2. Probability Concepts and Applications
3. Decision Analysis
4. Regression Models
5. Forecasting
6. Inventory Control Models
7. Linear Programming Models: Graphical and Computer Methods
8. Linear Programming Applications
9. Transportation, Assignment, and Network Models
10. Integer Programming, Goal Programming, and Nonlinear Programming
11. Project Management
12. Waiting Lines and Queuing Theory Models
13. Simulation Modeling
14. Markov Analysis
15. Statistical Quality Control

### APPENDICES

1. Areas Under the Standard Normal Curve
2. Binomial Probabilities
3. Values of for Use in the Poisson Distribution
4. F Distribution Values
5. Using POM-QM for Windows
6. Using Excel QM and Excel Add-Ins
7. Solutions to Selected Problems
8. Solutions to Self-Tests

### ONLINE MODULES

1. Analytic Hierarchy Process
2. Dynamic Programming
3. Decision Theory and the Normal Distribution
4. Game Theory
5. Mathematical Tools: Determinants and Matrices
6. Calculus-Based Optimization
7. Linear Programming: The Simplex Method
8. Transportation, Assignment, and Network Algorithms

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