Introduction to Management Science - Softcover

Anderson, David; Sweeney, Dennis J.; Williams, Thomas

9781408079577: Introduction to Management Science

Softcover

ISBN 10: 1408079577 ISBN 13: 9781408079577

Publisher: Cengage Learning EMEA, 2014

In the second edition of this highly-regarded text, the accessible application-driven approach that made the first edition so successful has been retained, whilst it has been streamlined and strengthened further to meet the needs of students across the UK, Europe, Middle East and Africa.

Packed with diverse realistic examples from Scotland to Saudi Arabia, this truly internationalized version of the landmark text from the Anderson, Sweeney and Williams team provides a comprehensive introduction to the subjects of Management Science and Operations Research.

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About the Author:

Dr. David R. Anderson is Professor Emeritus of Quantitative Analysis in the College of Business Administration at the University of Cincinnati. He earned his B.S., M.S., and Ph.D. degrees from Purdue University. Professor Anderson has served as Head of the Department of Quantitative Analysis and Operations Management and as Associate Dean of the College of Business Administration. In addition, he was the coordinator of the College's first Executive Program. At the University of Cincinnati, Professor Anderson has taught introductory statistics for business students as well as graduate-level courses in regression analysis, multivariate analysis, and management science. He has also taught statistical courses at the Department of Labor in Washington, D.C. He has been honored with numerous nominations and awards for excellence in teaching and excellence in service to student organizations. Professor Anderson has co-authored 10 leading textbooks in the areas of statistics, management science, linear programming, and production and operations management. He is an active consultant in the field of sampling and statistical methods. Dennis J. Sweeney is Professor of Quantitative Analysis and Director 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, graduating summa cum laude. He received his M.B.A. and D.B.A. degrees from Indiana University where he was an NDEA Fellow. During 1978-79, he spent a year working in the management science group at Procter & Gamble; during 1981-82, he was a visiting professor at Duke University. Professor Sweeney served 5 years as Head of the Department of Quantitative Analysis and 4 years as Associate Dean of the College of Business Administration at the University of Cincinnati. Professor Sweeney has published over 30 articles 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, athematical Programming, Decision Sciences, and other journals. Professor Sweeney has coauthored eight textbooks in the areas of statistics, management science, linear programming, and production and operations management. Dr. Thomas A. Williams is Professor Emeritus of Management Science in the College of Business at Rochester Institute of Technology. He earned his B.S. degree at Clarkson University. He completed his graduate work at Rensselaer Polytechnic Institute, where he received his M.S. and Ph.D. degrees. Before joining the College of Business at RIT, Professor Williams served for seven years as a faculty member in the College of Business Administration at the University of Cincinnati, where he developed the undergraduate program in Information Systems and then served as its coordinator. At RIT he was the first chairman of the Decision Sciences Department. He teaches courses in management science and statistics, as well as graduate courses in regression and decision analysis. Professor Williams is the co-author of 11 leading textbooks in the areas of management science, statistics, production and operations management, and mathematics. He has been a consultant for numerous Fortune 500 companies and has worked on projects ranging from the use of data analysis to the development of large-scale regression models.

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