Quantitative Methods for Business ( BST )

Publication series :BST

Author: David R. Anderson;Dennis J. Sweeney;Thomas A. Williams;Jeffrey D. Camm;James J. Cochran;Michael J. Fry;Jeffrey W. Ohlmann  

Publisher: Cengage‎

Publication year: 2016

E-ISBN: 9781305799257

P-ISBN(Paperback): 9781285866314

Subject: C93 Management

Keyword: 经济计划与管理

Language: ENG

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Description

Written with the non-mathematician in mind, QUANTITATIVE METHODS FOR BUSINESS, 13E by award-winning authors Anderson, Sweeney, Williams, Camm, Cochran, Fry, and Ohlmann equips your students with a strong conceptual understanding of the critical role that quantitative methods play in today's decision-making process. This applications-oriented text clearly introduces current quantitative methods, how they work, and how savvy decision makers can most effectively apply and interpret data. A strong managerial orientation motivates learning by weaving relevant, real-world examples throughout. The authors' hallmark "Problem-Scenario Approach" helps readers understand and apply mathematical concepts and techniques. Instant online access provides students with Excel® worksheets, LINGO, and the Excel add-in Analytic Solver Platform. Using Microsoft Excel to develop spreadsheet simulation models, the thoroughly revised Chapter 16 explains how to construct a spreadsheet simulation model using only native Excel functionality, while the chapter appendix covers how the use of Excel add-in Analytic Solver Platform facilitates more sophisticated simulation analyses. Data Tables and Goal Seek Excel features were also added to Appendix A to help in the construction of spreadsheet simulation models. The 13th Edition includes a more holistic description of how variable activity times affect the probability of a project meeting a deadline, while maintaining simplicity by showing when using the cri

Chapter

Chapter 2 Introduction to Probability

Chapter 3 Probability Distributions

Chapter 4 Decision Analysis

Chapter 5 Utility and Game Theory

Chapter 6 Time Series Analysis and Forecasting

Chapter 7 Introduction to Linear Programming

Chapter 8 Linear Programming:Sensitivity Analysis and Interpretation of Solution

Chapter 9 Linear Programming Applications in Marketing,Finance,and Operations Management

Chapter 10 Distribution and Network Models

Chapter 11 Integer Linear Programming

Chapter 12 Advanced Optimization Applications

Chapter 13 Project Scheduling:PERT/CPM

Chapter 14 Inventory Models

Chapter 15 Waiting Line Models

Chapter 16 Simulation

Chapter 17 Markov Processes

Appendix A Building Spreadsheet Models

Appendix B Binomial Probabilities

Appendix C Poisson Probabilities

Appendix D Areas for the Standard Normal Distribution

Appendix E Values of e-y

Appendix F References and Bibliography

Appendix G Self-Test Solutions and Answers to Even-Numbered Problems

Index

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