Description
By (author) Anderson, David; By (author) Sweeney, Dennis; By (author) Williams, Thomas; By (author) Fry, Michael; By (author) Ohlmann Jeffrey; By (author) Camm, Jeffrey; By (author) Cochran James
Short /annotation:
Suitable for the current-or future-business professional, this book makes it easy for you to understand how you can most effectively use quantitative methods to make smart, successful decisions. It guides you step by step through the application of mathematical concepts and techniques.
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You don”t have to be a mathematician to maximize the power of quantitative methods. Written for the current-or future-business professional, QUANTITATIVE METHODS FOR BUSINESS, 13E makes it easy for you to understand how you can most effectively use quantitative methods to make smart, successful decisions. The book”s hallmark problem-scenario approach guides you step by step through the application of mathematical concepts and techniques. Memorable real-life examples demonstrate how and when to use the methods found in the book, while instant online access provides you with Excel® worksheets, LINGO, and the Excel add-in Analytic Solver Platform. The chapter on simulation includes a more elaborate treatment of uncertainty by using Microsoft Excel to develop spreadsheet simulation models. The new edition also includes a more holistic approach to variability in project management. Completely up to date, QUANTITATIVE METHODS FOR BUSINESS, 13E reflects the latest trends, issues, and practices from the field.
Table of contents:
Preface.1. Introduction.2. Introduction to Probability.3. Probability Distributions.4. Decision Analysis.5. Utility and Game Theory.6. Time Series Analysis and Forecasting.7. Introduction to Linear Programming.8. Linear Programming: Sensitivity Analysis and Interpretation of Solution.9. Linear Programming Applications in Marketing, Finance, and Operations Management.10. Distribution and Network Models.11. Integer Linear Programming.12. Advanced Optimization Applications.13. Project Scheduling: PERT/CPM.14. Inventory Models.15. Waiting Line Models.16. Simulation.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 for e-?.Appendix F: References and Bibliography.Appendix G: Self-Test Solutions and Answers to Even-Numbered Problems.
Biographical note:
David R. Anderson is a leading author and professor emeritus of quantitative analysis in the College of Business Administration at the University of Cincinnati. Dr. Anderson has served as head of the Department of Quantitative Analysis and Operations Management and as associate dean of the College of Business Administration. He was also coordinator of the college’s first executive program. In addition to introductory statistics for business students, Dr. Anderson taught graduate-level courses in regression analysis, multivariate analysis and management science. He also taught statistical courses at the Department of Labor in Washington, D.C. Dr. Anderson has received numerous honors for excellence in teaching and service to student organizations. He is the co-author of ten well-respected textbooks related to decision sciences and he actively consults with businesses in the areas of sampling and statistical methods. Born in Grand Forks, North Dakota, Dr. Anderson earned his B.S., M.S. and Ph.D. degrees from Purdue University. Dennis J. Sweeney is professor emeritus of quantitative analysis and founder of the Center for Productivity Improvement at the University of Cincinnati. Born in Des Moines, Iowa, he earned a B.S.B.A. degree from Drake University and his M.B.A. and D.B.A. degrees from Indiana University, where he was an NDEA fellow. Dr. Sweeney has worked in the management science group at Procter & Gamble an
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