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Quantitative methods for business / David R. Anderson, University of Cincinnati, Dennis J. Sweeney, University of Cincinnati, Thomas A. Williams, Rochester Institute of Technology, Jeffrey D. Camm, University of Cincinnati, Kipp Martin, University of Chicago.

By: Contributor(s): Australia : South-Western, Cengage Learning, ©2013Edition: 12e [edition], International editionDescription: xxv, 880 pages : illustrations (colour), maps (colour) ; 26 cmISBN:
  • 9781133584469 (paperback) :
  • 1133584462 (paperback) :
Subject(s): DDC classification:
  • 23 658.4033/An23
Other classification:
  • Grad
Contents:
1. Introduction. 2. Introduction to Probability. 3. Probability Distributions. 4. Decision Analysis. 5. Utility and Game Theory. 6. 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. Appendixes A-G. Index.
Summary: This edition of 'Quantitative Methods for Business' provides students with a conceptual understanding of the role played by quantitative methods in the decision-making process.
Holdings
Item type Current library Collection Call number Status Barcode
Books Books College Library General Circulation Section GC Grad 658.4033/An23 (Browse shelf(Opens below)) Available 80035

Includes internet access.

Textbook resources access card in envelope bound in.

Formerly CIP. Uk

Includes bibliographical references and index.

1. Introduction. 2. Introduction to Probability. 3. Probability Distributions. 4. Decision Analysis. 5. Utility and Game Theory. 6. 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. Appendixes A-G. Index.

This edition of 'Quantitative Methods for Business' provides students with a conceptual understanding of the role played by quantitative methods in the decision-making process.

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