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.
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.
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.
Inhaltsangabe
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.
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.
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