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Quantitative Methods for Business [With Access Code]


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Table of Contents

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.

About the Author

Dr. David R. Anderson is a leading author and Professor Emeritus of Quantitative Analysis in the College of Business Administration at the University of Cincinnati. He 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 has taught graduate-level courses in regression analysis, multivariate analysis, and management science. He also has 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 actively consults with businesses in the areas of sampling and statistical methods. Born in Grand Forks, North Dakota, he 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 BSBA degree from Drake University and his MBA and DBA degrees from Indiana University, where he was an NDEA Fellow. Professor Sweeney has worked in the management science group at Procter & Gamble and has been a visiting professor at Duke University. Professor Sweeney served as Head of the Department of Quantitative Analysis and four years as Associate Dean of the College of Business Administration at the University of Cincinnati. Professor Sweeney has published more than 30 articles and monographs in the area of management science and statistics. The National Science Foundation, IBM, Procter & Gamble, Federated Department Stores, Kroger and Cincinnati Gas & Electric have funded his research, which has been published in Management Science, Operations Research, Mathematical Programming, Decision Sciences and other journals. Professor Sweeney has co-authored ten textbooks in the areas of statistics, management science, linear programming and production and operations management. N/A Jeffrey D. Camm is the Inmar Presidential Chair and Associate Dean of Analytics in the School of Business at Wake Forest University. Born in Cincinnati, Ohio, he holds a BS from Xavier University (Ohio) and a PhD from Clemson University. Prior to joining the faculty at Wake Forest, he was on the faculty of the University of Cincinnati. He has also been a visiting scholar at Stanford University and a visiting professor of business administration at the Tuck School of Business at Dartmouth College. Dr Camm has published over 40 papers in the general area of optimization applied to problems in operations management and marketing. He has published his research in Science, Management Science, Operations Research, Interfaces and other professional journals. Dr Camm was named the Dornoff Fellow of Teaching Excellence at the University of Cincinnati, and he was the 2006 recipient of the INFORMS Prize for the Teaching of Operations Research Practice. A firm believer in practising what he preaches, he has served as an operations research consultant to numerous companies and government agencies. From 2005 to 2010 he served as editor-in-chief of Interfaces. In 2017, he was named an INFORMS Fellow. James J. Cochran is Professor of Applied Statistics and the Rogers-Spivey Faculty Fellow at the University of Alabama. Born in Dayton, Ohio, he earned his BS, MS, and MBA degrees from Wright State University and a PhD from the University of Cincinnati. He has been at the University of Alabama since 2014 and has been a visiting scholar at Stanford University, Universidad de Talca, the University of South Africa, and Pole Universitaire Leonard de Vinci.

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